mixed_effects_model_tutorial.ipynb

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    {
      "cell_type": "markdown",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/foxtrotmike/CS909/blob/master/mixed_effects_model_tutorial.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "cell_type": "markdown",
      "source": [
        "# Mixed Effect Model Tutorial\n",
        "(Fayyaz Minhas)\n",
        "## Objective\n",
        "Understand the application of negative binomial and Tweedie mixed-effect models in scenarios with overdispersed count data and data that could benefit from the flexibility of Tweedie distribution, respectively.\n",
        "\n",
        "## Scenario\n",
        "Suppose we are studying the effect of an environmental factor (x) on the count of a particular event (y), measured across different locations (p) with multiple observations per location. We suspect overdispersion in the count data and potential zero inflation, making the negative binomial and Tweedie distributions appropriate choices.\n",
        "\n",
        "## Step 1: Install and Load Necessary Packages\n",
        "Ensure glmmTMB and ggplot2 are installed and loaded into your R session."
      ],
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      "cell_type": "code",
      "execution_count": 37,
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        "id": "vCfEoyT3_CtC"
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      "outputs": [],
      "source": [
        "# install.packages(c(\"glmmTMB\", \"ggplot2\"))\n",
        "library(glmmTMB)\n",
        "library(ggplot2)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 2: Generate Synthetic Data\n",
        "We'll generate synthetic data that mimics overdispersion in count data."
      ],
      "metadata": {
        "id": "2n4OFzAK_Q7r"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "set.seed(123) # For reproducibility\n",
        "n_locations <- 50\n",
        "n_observations <- 200\n",
        "\n",
        "# Generate location IDs\n",
        "location_id <- rep(1:n_locations, each = n_observations)\n",
        "\n",
        "# Simulate environmental factor (x) randomly\n",
        "environmental_factor <- runif(n_locations * n_observations, 0, 5)\n",
        "\n",
        "# Random effects for locations\n",
        "random_effects <- rnorm(n_locations, 0, 2)\n",
        "location_effect <- random_effects[location_id]\n",
        "\n",
        "# Generate count data (y) with overdispersion\n",
        "y <- rnbinom(n_locations * n_observations, size = 2, mu = exp(2 - 2 * environmental_factor + location_effect))\n",
        "\n",
        "data <- data.frame(location_id, environmental_factor, y)\n"
      ],
      "metadata": {
        "id": "j-XW7cQI_SLM"
      },
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 3: Fit Mixed-Effect Models\n",
        "Negative Binomial Regression"
      ],
      "metadata": {
        "id": "UCG8hRia_VuT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "nb_model <- glmmTMB(y ~ 1 + environmental_factor + (1|location_id), data = data, family = nbinom2)\n",
        "summary(nb_model)\n",
        "tweedie_model <- glmmTMB(y ~ 1 + environmental_factor + (1|location_id), data = data, family = tweedie)\n",
        "summary(tweedie_model)\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
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        },
        "id": "zDcVP4U1_Xg-",
        "outputId": "ac283d14-7dd9-4b23-b172-db86ee6c05a3"
      },
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              " Family: nbinom2  ( log )\n",
              "Formula:          y ~ 1 + environmental_factor + (1 | location_id)\n",
              "Data: data\n",
              "\n",
              "     AIC      BIC   logLik deviance df.resid \n",
              " 16061.3  16090.1  -8026.6  16053.3     9996 \n",
              "\n",
              "Random effects:\n",
              "\n",
              "Conditional model:\n",
              " Groups      Name        Variance Std.Dev.\n",
              " location_id (Intercept) 3.675    1.917   \n",
              "Number of obs: 10000, groups:  location_id, 50\n",
              "\n",
              "Dispersion parameter for nbinom2 family ():  1.9 \n",
              "\n",
              "Conditional model:\n",
              "                     Estimate Std. Error z value Pr(>|z|)    \n",
              "(Intercept)           1.98372    0.27325    7.26 3.88e-13 ***\n",
              "environmental_factor -2.06821    0.02336  -88.55  < 2e-16 ***\n",
              "---\n",
              "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              " Family: tweedie  ( log )\n",
              "Formula:          y ~ 1 + environmental_factor + (1 | location_id)\n",
              "Data: data\n",
              "\n",
              "     AIC      BIC   logLik deviance df.resid \n",
              " 17547.8  17583.8  -8768.9  17537.8     9995 \n",
              "\n",
              "Random effects:\n",
              "\n",
              "Conditional model:\n",
              " Groups      Name        Variance Std.Dev.\n",
              " location_id (Intercept) 3.709    1.926   \n",
              "Number of obs: 10000, groups:  location_id, 50\n",
              "\n",
              "Dispersion parameter for tweedie family (): 2.76 \n",
              "\n",
              "Conditional model:\n",
              "                     Estimate Std. Error z value Pr(>|z|)    \n",
              "(Intercept)           1.96265    0.27478    7.14 9.15e-13 ***\n",
              "environmental_factor -2.04792    0.02102  -97.42  < 2e-16 ***\n",
              "---\n",
              "Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Step 4: Generate Plots\n",
        "To visualize the effects and clarify the concept of mixed-effect models, we can plot the observed counts vs. the environmental factor, highlighting the random effects by location.\n",
        "\n",
        "### Observed Counts vs. Environmental Factor\n",
        "\n",
        "\n"
      ],
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        "id": "quTLwMVr_bqZ"
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    },
    {
      "cell_type": "code",
      "source": [
        "ggplot(data, aes(x = environmental_factor, y = y)) +\n",
        "  geom_point(alpha = 0.5) +\n",
        "  geom_smooth(method = \"glm\", method.args = list(family = \"quasipoisson\"), se = FALSE, color = \"blue\") +\n",
        "  labs(title = \"Observed Counts vs. Environmental Factor\", x = \"Environmental Factor\", y = \"Count\") +\n",
        "  theme_minimal()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 455
        },
        "id": "J8fZQIte_eou",
        "outputId": "c8bae0ae-a886-46ee-f395-4adc6f032a88"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\u001b[1m\u001b[22m`geom_smooth()` using formula = 'y ~ x'\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "plot without title"
            ],
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UscDsfll18eHh6+b9++rl27/vGPf3S7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Ph8vlAoLCoqkkqlzc3N6JJsaWmxWq0YZrdx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"
          },
          "metadata": {
            "image/png": {
              "width": 420,
              "height": 420
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "This plot shows the raw data with a generalized linear model fit, approximating the expected trend. The spread of points around the trend line hints at overdispersion and the potential suitability of negative binomial or Tweedie models.\n",
        "\n",
        "### Visualizing Random Effects\n",
        "\n",
        "While it's challenging to directly visualize random effects, we can examine the variability in counts by location."
      ],
      "metadata": {
        "id": "x4ZWAh9X_iEd"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ggplot(data, aes(x = factor(location_id), y = y)) +\n",
        "  geom_boxplot() +\n",
        "  labs(title = \"Count Variability by Location\", x = \"Location ID\", y = \"Count\") +\n",
        "  theme_minimal() +\n",
        "  theme(axis.text.x = element_text(angle = 90, hjust = 1))\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 437
        },
        "id": "bW_w6Umz_m5Y",
        "outputId": "24d06428-47d0-40d5-a158-475749b167f6"
      },
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "plot without title"
            ],
            "image/png": 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JfamTZrOqjurGyYdVdi1l2aGqz+UQkJ\nUnWFUKlbVkEUdUuoWVHkGmapW07NcrfU9C4yzJIA72LLO0rNMtM76treFaZ3WTLv5NkIyHRQ\nNuxMR5N5J2TDynRZMu9i0zug7orNhFne5Xambe9oMm83INOpZCOg7ortugvRYKPx2tD3Cbi1\noyZu7XBrx4VnJIDkASQmgASQmAASQAqdLoAEkJgAEkBiAkgAKWUBJIDEBZDCCSABJC6AFE4A\nCSBxAaRwAkgAiQsghRNAAkhcACmcABJA4konSKVbDhnRAAkgeQCJKRWQque3cZyZ9HAACSB5\nAIkpFZDmOEwXkowBJIDkASSmFED60RH6SEcDJIDkASSmFED6UIK0SkcDJIDkASSmFEDaJUF6\nS0cDJIDkASSmFEBqmMA5GkCqDyABJA8gMaXS2bDvbJ+jM3aQaIAEkDyAxJTSOFLsrfvXG/kA\nSADJA0hMmNkQJIAEkLgAUjgBJIDEBZDCCSABJC6AFE4ACSBxAaRwAkgAiQsghRNAAkhcACmc\nABJA4gJI4QSQABIXQAongASQuABSOAEkgMQFkMIJIAEkLoAUTgAJIHEBpHACSACJCyCFE0AC\nSFwAKZwAEkDiAkjhBJAAEhdACieABJC4AFI4ASSAxAWQwgkgASQugBROAAkgcQGkcAJIAIkL\nIIUTQAJIXAApnAASQOICSOEEkAASF0AKJ4AEkLgAUjgBJIDEBZDCCSABJC6AFE4ACSBxAaRw\nAkgAiQsghRNAAkhcACmcABJA4gJI4QSQABIXQAongASQuABSOAEkgMQFkMIJIAEkLoAUTgAJ\nIHEBpHACSACJCyCFE0ACSFwAKZwAEkDiAkjhBJAAEhdACieABJC4AFI4ASSAxAWQwgkgASQu\ngBROAAkgcQGkcAJIAIkLIIUTQAJIXAApnAASQOICSOEEkAASF0AKJ4AEkLgAUjgBJIDEBZDC\nCSABJC6AFE4ACSBxAaRwAkgAiQsghRNAAkhcACmcABJA4gJI4QSQABIXQAongASQuABSOAEk\ngMQFkMIJIAEkLoAUTgAJIHEBpHACSACJCyCFE0ACSFwAKZwAEkDiAkjhBJAAEhdACieABJC4\nAFJTWjdpyEUf+BW7eNyoOQf1pyWABJC4AFITem3sloPPT67y5s7cvW/RtPr4pyWABJC4AFIT\nmryBf7gDd/mVO3ir+rTdABJA4gJIjatowIaLh13xhbdpKCv7i55Un7YfQAJIXACpcX01YNb3\n0ftGlK0fz6zZ96nP+BmiQqVuaZSo3C2mZrTINcxSt8z0LknmXeKWm96lprd5qmLTOyBhxQEJ\nS5qNkhSzYXiX2d5Flnd5Mm83wLs0mXfyTEeTJ6w0g9koDshGWms6LQ1W/4oEguTfxcVGvrZ+\nggRpgglSmQtBrVf6ihoAkjtgp/932tPvi1u6+KeKr48JVbrVMaI6t5yaseIiw6x0a03vCtO7\n2DCjbh01a91KI7qoxDDLTe9q0/uIW2p4l7lHqFllZuOwW2Z4l7iGWeHWULPOjZreRZa3kela\nO9NmNqLuYWrWWN6unWnDu9qtoqad6VIz05V2ps26K7HrLnmmzbqrsOvOzEbyuquxajqh7oxM\nV5mZtuuu1Ky7NDVYfXMZAFL92DX+verZG4sH+kCVD9quPm0/PCPhGYkLz0hN6OnRn7h3jK3x\nFly2+4cbpzfEPy0BJIDEBZCaUP3KMUOu3usfasnY0fNL9KclgASQuABSOAEkgMQFkMIJIAEk\nLoAUTgAJIHEBpHACSACJK40g7bp58vWf0miABJA8gMSUCkhvt3d8PU2iARJA8gASUwog1fVm\nHDkdyZIdgASQPIDElAJInzlCL+pogASQPIDElAJIn0iQ1uhogASQPIDElAJIVZ0FSHt0NEAC\nSB5AYkqls+E5ztFdJBogASQPIDGl1P39zgX9z1tHUwqQAJIHkJgwIBskgASQuABSOAEkgMQF\nkMIJIAEkLoAUTgAJIHEBpHACSACJCyCFE0ACSFwAKZwAEkDiAkjhBJAAEhdACieABJC4AFI4\nASSAxAWQwgkgASQugBROAAkgcQGkcAJIAIkLIIUTQAJIXAApnAASQOICSOEEkAASF0AKJ4AE\nkLgAUjgBJIDEBZDCCSABJC6AFE4ACSBxAaRwAkgAiQsghRNAAkhcaQRp35JLbt1JowESQPIA\nElMqIH3Q0XGcDutINEACSB5AYkoBpCP9+E6rXcjZAVLrBKnooGECpJRA2i430V+vowFSawRp\n59QO7SfvIAEAKSWQPpIgvaCjAVIrBOlgD35j8p0OAUgpgRTtIEDapaMBUisEaZ5oBlfpEICU\nWmfDo7wAF5FogNQKQZogQBqiQwBSaiA1vDym2zlP0lIASK0QpGkCpHN1CEDCgGywAJIFknhN\nlvOwDgFIAClYAMkCqeEaxtElJC0ACSAFCyAljCO9t/CWt6gNkABSsAASZjZwAaRwAkgAiQsg\nhRNAAkhcACmcABJA4gJI4QSQABIXQAongASQuABSOAEkgMQFkMIJIAEkLoAUTgAJIHEBpHAC\nSACJCyCFE0ACSFwAKZwAEkDiAkjhBJAAEhdACieABJC4AFI4ASSAxAWQwgkgASQugBROAAkg\ncQGkcAJIAIkLIIUTQAJIXAApnAASQOICSOEEkAASF0AKJ4AEkLgAUjgBJIDEBZDCCSABJC6A\nFE4ACSBxAaRwAkgAiQsghRNAAkhcACmcABJA4gJI4QSQABIXQAongASQuABSOAEkgMQFkMIJ\nIAEkLoAUTgApEST3R8MESAApWADJBunrC9u3m7idBAAkgBQsgGSB9GMP9g7Zzt/qEIAEkIIF\nkCyQ5om3ms/QIQAJIAULIFkgTRAgDdEhAAkgBQsgWSBNEyCN0SEACSAFCyBZIK0SIK3UIQAJ\nIAULIFkgNcxmHF1GqhogAaSmVR8TqnSrY0R1bjk1Y8VFhlnp1preFaZ3sWFG3Tpq1rqVRnRR\niWGWm97VpvcRt9TwLnOPULPKzMZht8zwLnENs8KtoWadG6Xme7fd8qbpbWS61s60mY2oe5ia\nNZa3a2fa8K52q6hpZ7rUzHSlnWmz7krsukuW6ViJWXcVdt2Z2UhedzVWTSfUnZHpKjPTdt2V\nmnWXpgarUQ4JUkWpULFbXEpU4hZRs9R1DbPYLTG9i5N5FwV4F6XgbSesyDxVifnlxGMbZrHt\nbSYsubedjaIiy9tKWNJMJ3inMxv2qaxspHLsgHYRqqYDmmBCwtLSYPVVD7d21MQUIdzaceEZ\nCSB5AIkJIAEkJoAEkEKnCyABJCaABJCYABJASlkACSBxAaRwAkgJIG1ZetsmagMkgBQsgGTP\nbLiBzWy4AjMbAFJKAkgWSKvFXLtHdAhAAkjBAkgWSBdh9jcTQEpRAMkCaTzWIzEBpBQFkCyQ\n5mKFLBNASlEAyQJpf3e+Z8MuHQKQAFKwAJLd/f3l5LZtxn9KAgASQAoWQEockD14wDABEkAK\nFkDCzAYugBROAAkgcQGkcAJIAIkLIIUTQAJIXAApnACSDVLV8gnj7qSlAJAAUrAAkgVSzXA2\njjSAFANAAkjBAkgWSPeImQ236hCABJCCBZAskCYJkIbrEIAEkIIFkAASF0AKJ4CEWzsugBRO\nAKnxzgbyfYAEkIIFkBK6v+8dP+YO+nWABJCCBZAwIMsFkMIJIAEkLoAUTgAJIHEBpHACSACJ\nCyCFE0ACSFwAKZwAEkDiAkjhBJAAEhdACieABJC4AFI4ASSAxAWQwgkgASQugBROAAkgcQGk\ncAJIAIkLIIUTQAJIXAApnAASQOICSOEEkAASF0AKJ4AEkLgAUjgBJIDEBZDCCSABJC6AFE4A\nCSBxAaRwAkgAiQsghRNAAkhcACmcABJA4gJI4QSQABIXQAongASQuFoiSA3rppw1YwcJAEgA\niQkgpdZgF/HdpzfqAIAEkJgAUkoN9kuxjXs3nTaA1EpAKvrgEDUBkhcGpMUCJOfLeAhAahUg\nVdxY4BRcQ1IOkLwwIM2QIL0RDwFI2QTJXb3qR2pnDaSrebVfqjMGkLwwIN0tQfo2HgKQsgjS\nox0dp8NyEpAtkL6V9a67mQCSFwakPW15efbThQaQsgfSe6I1v6xDsgXSRgnS+ngIQPJC9do9\nyoqz03YdAJCyB9IVojVP0iHZAmm7BOmDeAhA8sINyH4296I7DhIbIGUPpHGiNQ/WIdkCqX4U\nP/MwfTaA5GFmg5enIM0SIE3VIVnrbNgzlBG8UwcAJA8geXkK0vYOHKTNOiR740hH3ljxGk0Z\nQPIAkpenIHmv9HacHqtJAGY2AKRgAaSEcaS6zZuMmgVIAClYACl3ZjYAJCaABJCYABJACp0u\ngASQmAASQGICSAApZQGkBJDemDfnFXpwgASQggWQLJDqr2TDSBeSlAMkgBQsgGSB9JSY2fCA\nDgFIAClYAMkCaYoA6RwdApAAUrAAkgVSfwFSdx0CkPIVpNrlAzuMeoUEAKTsgXS6AKmrDgFI\n+QqSWHK8SgcApNawjMIDSEzpA+kjUZVddL4BUvZAkgv9b9EhAClPQXpUrpT8Oh4CkLIHUvUw\nVvZnku8DpDwF6VkJ0t54CEDK4oBs1d1jR99Ovw6Q8hSkfR05R2dj8xMiTBHy8gaksodvXH6A\nRjdXZwO/JPX4SgcAJIDElB8g7ejB9u55i0Q32zjSV7fNuI8WOEACSEx5AVL9YH5D1YMkHQOy\nAMkDSEwpgPS5fMR/VUcDJIDkASSmFECSozcO2fYCIAEkDyAxpQBSqdgo2PlCRwMkgOQBJKZU\nOhuWc45uINH5DtJrA97zK3bxuFFzDupPSwAJIHGlD6T6x890+txLk5bnIJWOGeqDNHfm7n2L\nptXHPy0BJIDEldYB2f05MSDrpQmkBSvGvOe5A3f5lTt4q/q0nQASQOJqgTMbvPSAtGlSjQ/S\npqGs7C96Un3aXgAJIHEBpCZUMfYTzwdp/XhmzL5Pfaro2mqhcjdaTVTpllKzuqjIMMvdCtO7\nLJl3qVtJzQq33PQuTuYdNb2r3BLDu8StNr2jybyLTe+y5NlI7l1hZ9rORlUybzepd0A2Skzv\nctvbrLvigLpL6l1m111ANpLWdIrZSFrTaWqwmt0gkJYu9ThIEyRIE0yQylwIar3SV1QDJOdz\n8fnMv6mQT8ZGOUjvi1u6p9Wnij9cKxR1K2qJqt1SatYWFxlm1K2iZpVbbkQXmd5ltnfU9C6x\nvKupWWF617imd6lbY3pXmt5WNlzDLDe9q90y07vI8k6e6WLDtLJRaXm7dqZrTG+jNuxMl5je\nUdvbzEaJXXdGpquCMl1teifNdKmdabOmg+rOyoZZdyVm3aWpwerbXAOkyBb+cWTOiSpk4dBR\no0YNPHt+8cCd/k3poO3q075w4RkJz0hceEby/9X6kwqLsuvXua+Uewsu2/3DjdMb4p+WABJA\n4gJInrf19sigiUyTrv/e8PFv7byqJWNHzy/Rn5YAEkDiapkgff++cerAXru+XyfEH6UAEkDi\naokg7Z/qOG0XkWxjrh1AYgJIKTXYw6P5rL/FOiQQpIPjfnO8eEhK8AsQQEoA6ZuVD35JbYCU\npyC9Iaaht9XHCwRp+E96jeNPSRMT/AIEkGyQbmeFP48cHSDlKUiPyJVR+mcxEKS/fT4h/igF\nkCyQXhWF/6wOAUh5CtI6CdKheEggSCcfSog/SgEkC6RLReGP1yEAKU9BKu/Lq/IyHRIIUpc3\nEuKPUgAJWxZztUCQvI/7+TU5gWQsEKQP225KcDg6ASQLpOsd+2cMIOUrSF7VKw9tpkUWCFKn\n30ZO/meuBL8AASQLpN2dGUcdyFwqgJS3IKW8jKJLL6UEvwABJLvX7oOhjjNgIwkASK0HpGMX\nQLJBeneA4/TbQAIAEkAKFkCyQNrJd17vQNbkA6TWA9LfKv0iwS9AAMkC6VrR2XCxDgFIrQek\nQVxtf/6HaQl+AQJI6P7mAkhEB7qubSQ0qQCSBdJlAqQJOgQgtTqQvC1OY6HJBJAskN5M2Lka\nILU+kA78vLHQZAJIdq/dve3NqfcAyWt1IDXM+1+NhCYVQEpYRrH38Ud2URsgtR6Q/sj1h19F\nrkzwCxBAwsI+LoDEJED6n5631yX4BQggASQugBROAAkgcQEkoaK19z2wPprgFSiABJC4ABI/\n+RU/ZRs2nLIwwS1IAAkgcQEkpoWRISteXLu8b2Rlgl+AABJA4gJITP82XXye/6cEvwABJIDE\nBZCYTpLT/tdhQJYLIHkAiSlVkE5ZIz6fPzXBL0AACSBxASSmzj14IdX06Z7gFyCABJC4ABLT\nuuP+9wVzb5r8m+NfTfALEEACSFwAiWvV71n393+uS3ALEkACSFwASWrfB1t+THAKFkACSFwA\nydcBsdHqe8UJXoECSACJCyB53pq/WsI/f/d3nyS4BQkgASQugOR9fco/iWGkd3/9j4mv5AsQ\nQAJIXADJu+SnX8j/PjnhpgS/AAEkgMQFkLzfjYj/O+j3CX4BAkgAiQsgeafMi/8756QEvwAB\nJIDEBZC8UxbE/70BG0RyASQPIDGlBNIfzor/2/2/EvwCBJAAEhdA8q464UP535rItQl+AQJI\nAIkLIHk//s2vHmf5qF7y879LeUgWIAEkLoDkeW//KvK3PQd1OTXy6w8S3IIEkAASF0Dy9eOs\nfz8h8pP/uhFThKQAkgeQmFKftNpQ2ZDgcjQCSACJCyCFE0ACSFwAKZwAEkDiAkjhBJAAEhdA\nCieAZINUcefokYvpyQASQAoWQLJAqjqLvWesPzkbQAJIwQJIFkjLxBv75usQgASQggWQLJAm\nCpCG6RCABJCCBZAskCYLkIbrEIAEkIIFkCyQlguQbtMhAAkgBQsgWSDVjWQcDSYZA0gAKVgA\nye7+rnlw0sTlNKUACSAFK6V07Syc+QAtkxYJEgZkmcKA5N478/Y9NBogmela1d6/6enxddPp\nAkgAyfO2dvGbSQe6Cz1AMtK1rxN/DD9HVyZA8gASE6272Jm8mXQlHgDJSNezoj/L2dtkugAS\nQPJ2yGbyso4GSEa6HpUlpO/tAJIHkJho3X0km8lqHQ2QjHTJEuqi6wMgeQCJidZdeXv79xYg\nWem6ihfQs02nCyABJM97iDeTeSQaIJnpqrn3zPYj1idJF0ACSH6qVw1rP/BhWmYAqTUOyAIk\nJgzIpiiABJC4AFI4AVyFLB0AACAASURBVCSAxAWQwgkgASQugBROAAkgcQGkcAJIAIkLIIUT\nQAJIXAApnAASQOICSOEEkAASF0AKJ4AEkLgAUjgBJIDEBZDCCSABJC6AFE4ACSBxAaRwAkgA\niQsghRNAAkhcACmcABJA4gJI4QSQABIXQAongASQuABSOAEkgMQFkMIJIAEkLoAUTgAJIHEB\npHACSACJCyCFE0ACSFwA6dgULREqdotLiIrdImqWuG6JGV1sRlum6V0U4G2eqiggJbZ38oQl\nzUZCwlLxthNWFJCwgGNb3gEFmixhCUVkmgE1nZASywyVjYCaTi1haWmwGm1ckaiJKxKuSFy4\ntQNIHkBiAkgAiQkgAaTQ6QJIAIkJIAEkJoAEkFIWQAJIXAApnAASQOICSOEEkAASF0AKJ4AE\nkLgAUjgBJIDEBZDCCSABJC6AFE4AyQapctmY0Uvp1wESQAoWQLJAqh7G3sl9Jvk+QAJIwQJI\nFkh385fbOwt0CEACSMECSBZIkwRIw3UIQAJIwQJIAIkLIIUTQLJAWi5AWqhDABJAChZAskD6\nUIC0QYcAJIAULIBkgTRCgHSGDgFIAClYAMkCqb0AqY0OAUgAKVgAyQKprQCpQIcAJIAULIBk\ngXSaAKmrDgFIAClYAMkC6XkB0oM6BCABpGABJAukaDfGUUeSb4CUryDV3HNGuxHrSQBAyh5I\nS8UVaY4OAUj5CtLlvCqf0QEAKXsgnSdAGqpDAFKegrRFVGV7/QWAlD2Qzhelf44OAUh5CtI8\nUZXOp/EQgJQ9kB4ShX+7DgFIeQrSTAnSW/EQgJQ9kI5MYGU/gtQtQMpTkB6WIO2LhwCkLK6Q\nPfLUZZc8SuMBUp6CdKgj52iEDgFI2LOBCSCl1mA3MJL6f68DABJAYgJIKTbYHx9a8Bx1B0gA\niQkgYWaDB5C4ABJACk4XQAJITAAJILF0frjZiAZIAClYAMkGaUNfx+m1jgQAJIAULIBkgfR5\nBz74sEWHACSAFCyAZIE0S4yGT9MhAAkgBQsgWSCNEyAN0iEACSAFCyBZIE0XIE3UIQAJIAUL\nIFkgLRQgXaNDABJAChZAskCaKkA6V4cAJIAULIBkgTRBgDREhwAkgBQsgGSBJJdVztQhAAkg\nBQsgWSAd7ME46vKdDgFIAClYAMme2fDNtPbtJ+8gAQAJIAULICVOWi360TABEkAKFkDC7G8u\ngBROAAkgcQGkcAJIAIkLIIUTQAJIXAApnAASQOICSOEEkAASVxpBem18r1HP0nwBJIDkASSm\nVEB6gk8NWUyiARJA8gASUwogVYglxs4uHQ2QWiVIVe+8aWQLIKUE0sdyx+0XdDRAao0grevh\nOF2fJgEAKSWQtkmQ1utogNQKQfpUNIN3dQhASgmkw315AXYmRQ6QWiFI8qU6F+oQgJRaZ8P7\n/CFpNYkGSK0QpCECpNN0CEBKsfv7h9umzfuSRgOkVghSHwFSNx0CkDAgGyyAZIE0TIDUV4cA\nJIAULIBkgXSdAOlSHQKQAFKwAJIF0mcFHKSNOgQgAaRgASQLpCXiijRHhwAkgBQsgGSBdJ4A\naagOAUgAKVgAyQLpfMd+FTZAAkjBAkgWSA8LkO7QIQAJIAUrT0Bq2Lhk+U4anTGQjvB7u5Gk\nbgESQApWfoBUdwFr3feT6MxNWo09c/mlj9F4gASQgpUfIC0V91sf6BCsRwJITAApJZBOFyDd\npEMAEkBiAkgpgdRJgDRDhwAkgMQEkFICaYwA6V4dApAAEhNASgmkzZyjfqQ+ABJAYgJIqXV/\nvz7EaXPhbhIAkAASE0BKdUB29yHDGyABJCaAlKszGzyAxBQGpPp3HtpgnAsgASQPIDGlAtL+\nkf7z7IAvSDRAAkgeQGJKBSQxf34QyUmzgbTnnhv/QhMOkAASU16AtEvua/eWjm4ukNax/Yz6\nkD4qgASQmPICpA8lSKt0dDOB9GNnnpDROgQgASSmvADpgATpIx3dTCA9J1PyfTwEIAEkprwA\nybuBt97zScaaCaS/SJC+iocAJIDElB8gRccVOM5Z+0h0M4Ek5sM4nfXhjwWk4kXnnn21z2LF\n4nGj5hzUn5YAEkDiSh9Id/Pmey2JbiaQGi7nKXlchxwLSJfP3LX/ttE13tyZu/ctmlYf/7QE\nkAASV9pAKmkjLgQ7dHRz9dpVLT2tYPDzpMyOAaTo/L2ed2jA1+7AXX7lDt6qPm0/gASQuNIG\n0kfyyYTsot+MA7L70zIg+8Wgkk1DWdlf9KT6jB/ysFCFW3WYqNYto+bh4iLDrHCrqVnjRo3o\nItO73K2hZrVbYXqXGGaZW0vNKtO7zi21vOuoWWlnw/QucQ0zamaj1i03oq1MW97VVqaLiw2z\n3M6G6e3ama4zvSupaWe61PS26q7OqrsSu+4M7xo702Y2onbdWTVtetO62yZBellHJ2TDKKJK\nM9N2Eyw16y5dDTYVkKJTH/LWj2f/zb5Pfaq4MheCMqGDAzlHPXY3d0KSSl9Rg0H6/vy7G7z1\nEyRIE0yQaquFyt1oNVGlW0rN6qIiwyx3K0zvsmTepW4lNSvcctO7OJl31PSucksM7xK32vSO\nJvMuNr3LkmWj8vlrZz1d0bR3hZ1pOxtVybzdpN4B2Sgxvcttb7PuigPqLql3mV13Adkg3lt7\n+Rx12UC9U8tG0ppOU4PVd5OBIG0dtcb/+764pXtafdpeeEaynpHqp7Hf0wnEAc9IKc7+Ln90\nzgqjfzivJ63uGPkh+ygeuNNP+aDt6tN2A0gWSI+KO/x7dAhAas3rkeomP85uBWu8BZft/uHG\n6Q3xT0sAyQLpAgHSSB0CkFozSFsHcK31qpaMHT3fz7b6tASQLJAmCJDO0iEAqTWDdLQCSBZI\niwRI1+kQgASQggWQLJBK+NvtexzQIQAJIAULINkzG/bN7t1zxh4SAJAAUrAAEqYIcQGkcAJI\nAIkLIIUTQAJIXGkE6dDdVy2l98YACSAxAaTUQPqki+M4HV4h0QAJIHkAiSkFkI6cyccPupLj\nASSA5AEkphRA2qGWUejoZgTpEEACSPkJUg4t7Ku+8/Q2w9aSAIAEkJjyAqTy9gKkr3V0c4F0\nJU/IUzoAIGUTpOr3NhoJBUipdTas5M13HoluJpC2CKK76C8ApCyC9FIvx+n2LAkASKmB1LB6\nePvBK+nXmwmkR7Gvndd8IH3agRf+Jh0CkPJ0QPZZ7LTqNR9IV4vCv1CHAKQ8BelAJ3tpGUDK\nHkjjBEiDdAhAylOQvBdYv0evXToAIGUPJNHT40zWIQApX0Fa3c6vyZ47dQBAyh5IcsPoDToE\nIOUpSPvFrd0IHQKQsthr92Rnx+mwggQApBRBemty33Ev0JQ2c2fD3ngIQMrmOFLJi2sMd4CU\nGkii/d5OotH93SpBwswGLwxIleKGyvlWRzcTSB9iQNYDSEx5CdLH8jrwgo5uJpDqe/GETNch\nAAkgMeUFSJ9JkF7S0c0E0jsiIW11DQAkgMSUFyDV9ebNtyPZtLiZQJojkf4kHgKQABJTXoDk\nvcsnWdHZis0Ekpyk4rwdDwFI2QTprQXzNtCDA6QUu7+/mz/lRmOT+WYC6TEJkr42AqTsgdRw\nFSv7qSQtAClFkH647aJ5X9HoZgKptBvnaKIOAUjZA+kZ8StGRmQBUmogbe5gddo12xShzV39\nhJx1SAcApOyBNFWANFqHAKSUQDrM93x2OpMiby6QlrGEdNisAwBS1t9GMUSHAKSUQNoun0zW\n6+j9pne2QPpGJKSfPhtAyh5IN4jSv0yHAKRwA7KbR7XpcBndMDJbID0pU6LXUQCkrC/sm6JD\nAFJKIFWIJcbObmmLJcf9SE6yBdLjAMlrPpDEcKLTWYcApNQ6G57gBbhYmZNEgS7TDtkC6Utx\n5j5k80qAlDWQRJep016HAKQUu79fHd9z5DPxfHUXBXq5js9aZ8NifuaNOgAgZQ+ks0S9n65D\nsgdS9erbV1H3PAXJXNjXQxTopTokayA1vHjBWTN2kACAlD2QVol6f1CHZA2kr/r7J+5L5gS0\nCJB6igK9WIdg7+/WAFLDdfxGhFR1tkCKDeUtboDOSZ6CtH/ppQv1Rgndmu+KBJC85pxr98Hi\nhe9QO1sgfSo7md6Lh+QnSFvYyr7265R5tsjVLdoBILUOkJpr9vfbEiT9Goe8BOlIP56LLurs\nq7nZ6RvtDZAAkpdBkL6XIOn5nnkJUsLMhqsLHKft48Q7myDtB0itDiS5EG2WDshLkNRrXdTM\nhre41YEcPmsgVS7uXjDgOVJmAKlVgFSzuIPT4Vbin5cg7S8QIL0lbbFxgjNVe2cLpAYxAflR\nHQKQWgVIfsJ2GCnJS5DsF41Jrvpo72yB9L44czt9eIDUSkBqCTMb1DOS6jNpI8wztHe292zY\nGg8BSACJKS9AUr126njDRGteoL2zBdKEhG5QgNQ6QCp75OaVtAjzEiRvS0djHGk/fxXmGSSf\n2QLpcgnSu/EQgNQqQPqUzabpvkUH5CdI3v7bL7mVvAKi4qrTBy+h6GR7PZI+AEBqDSAdHsCr\nva/+Qp6C9M3ciddtpdHNtNS8vKfdXwiQWgNInyTcieQnSBv5vRx5l3iz7dnwCds+YjxJKkDK\nIkiH5pzZ/9p9JCBbIG2QID0XD8lLkOpOEyOwzb/Tqu/86soPaJEBpOyBVM7WMji9yB5O2QLp\nJQnSE/GQvARJ7f39oo5uNpAw1675QBKrKp0bdEi2QNokW+Br8ZC8BEllg6zoAkitECQ5+HCW\nDskWSKVi15B2+p4oL0F6RYK0UEcDpFYI0hTRDEbokKx1f4tdb8ger3kJktyq1rlZRwOkVgjS\nn0UzuEuHZG9A9q0p/c9/jdh5CdKbEqSlOhogtUKQYpNZKxhNDocpQimBJF8L7zymo5sNpB8f\nuuU56g6Qstj9Xf/8jCueotkESCmBtEuC9JaObi6QNnT203Hm9zoAILWGAVmvZYDUILprBpKc\nNBNIh7rylIzXIQAJIDHlBUjevnP81jvgcxLdTCA9L6+NenQdIAEkpvwAyYttXPGqkbJmAukv\nEiS9CQZAAkhMeQKSuUGkrz1m8WcLJDk03AFvNScCSF6+gvT2MKfthbtIQLZAqhd7NjysQwAS\nQGLKS5DEHg59yRey1mtXPq+z0+dRcrJcAenwpmfpM2QLBan4pbWGO0AKBdJ54gbrTh2SvXGk\nw+/+JWmDZWoGkL4Y4hfIxcShRYL0ZGf/tprMuARIXiiQmvG1LoENlin7IFWJFZxkA8OWCJIc\nmN+gQwBSKJBEq3Gu0yHZAim4wTJlH6T1okQKdIm3RJCuFLmcrEMAUiiQ7hIFqtf9Zg2k4AbL\nlH2Q5HRO58sm05U5kKoevPTql2kryhhI40QmB+kQgBQKpLoLWXmSN19mDaTgBsuUfZCekoDr\nys0aSKUDrGt0xl/GfKEOAUjhur8b3ll8z5c0OlsgvSqqsk3TDZYp+yCp3Y30JMCsgXSdOPN6\nHZIxkORbijbpEIAUdkC2mWY21Iq9KefqkNwA6XYJ0hdNpitjIPVs5IE1U712L/ZynG7PkgCA\nlKcgybsLsnlEboA0VYL0aZPpyhhIXcSZZ+qQzIH05cQ2bcZ8SgKyCFJ0q5FugOSFAWmHaDW9\ndE5yA6QREiS9YitrIF0ozkxe0JExkPbzcY9OZEpL1kCquqWt0+Zm+j5bgBQGpMdkg9W7vuYG\nSOqKpFdsZQ2kXey1pM5I0hIyBtJckckZOiRrIF1vnxkgeenYsvjbeEhugPSO7ARp+kqZue7v\nXTP6Di6kBZwxkMaLXA7RIdkCaU9Cby1A8sKA9K0ozwH6bLkBkrwkkb1oW+KA7EWi9MfoELyM\nOUWQalYvecoo/+bqbHiQFWeHT3RAjoDkrRzYfcRHxG6JIImXcDuP6JBsgaS2KN0cD7Ey/fHi\nuWvpwXMUpN1nsid82k6abfOTzbMn3/oDsbMGUvl9l83ZTKNzZRlFzZ+nX7eBRmcMpHrWDJze\nJJ/ZAik2nHM0WKfNBInvAXsuOVxuglQ/kmejL/lCq9uOa19vVgR3HHO6MgZS2SCWsGtJdMZA\nelZcFsj076x1NnzD5m/018N0Jkjyzu8WHZKbIH0lL6yv6+hWB5LsZSY3lTkC0g3200PmQJJ9\nk6N1SPbGkepeumudMbmGtkD5RtTeOiQ3QfpQgvS8jm5tINXI9+aSNVh2uvY1D0g9RMLIJSnT\ne383Q6+dl3xmw0yRsE46JDdB2leQM1ekuhWDu4wl6cgWSFH5W7K4iXRVLOrunPkMacB1n5ul\nnzGQ2oqEjdIhGQNpnjgVmUSRIyA9IBI2QYfkJkhysqKzVkc3F0gz7Utjtm7thiTcQdF0NVzC\nY+PTC+of7uq0mUHeJ5VxkEbqkIyBdJDP6+uyR4fkCEiVA3lnLpm8lJsgfZIzIH0sEtJR5ztb\nIInVoReSbNJ0vS/TpRr4Sm6OIa0sYyCJLTPpOorMzbXbdbHjTKEr/bMI0udrttFsmb12+2d2\nbjf2AxKQmyBVy4mRepFA0fq3jULIFkjzJdLb4iFZ6/7++IIeg5fRx90k++3VdUm4fmUMJLlI\naI0OyeQuQgO7GWbWQHIv8PM48YAOsAfPSvfnw4Cs2O3kzHjG7m3vOL3p2EW2QJouG2zTc9qY\nQoJUWSZU4paUEZW6xdQsc139/6MyXV8K83Np3ta4t69it9Q8tnGqMrcombeRsF28X35aKfUu\nM72tU5nHLgpImJnpgd2TJ8z0LrKzYSXMKtCmvUsn8fIcW9Kkd0I2rAJNmrCAmk7IRtIiSkiY\n9lbd329KW7z1qcMnjXsfRcLsAj3qBiv7jZyNxFt9WeMXEqT6mFClWx0jqnPLqRkrLtL/7xeX\noHOluU8m8xriXWx8OerWUbPWrTSii0oMs9z0rja8S+6cdOkzh0lAmXuEeleZ2TjslhnHLnEN\ns8KtoWadGzWiB3a3vGupWetWGNHFZjaiLk1mrMbydu1Ma+8vZIF+HA854pYa3qVmpivtTJt1\nV1IUM72TZrrErLsKu+7MbCSpO/Val2elLYaZnfnau8wsoiq3ysyGWXelZt2l0GDlaI7zEvFW\n2dDXxGaYIrSevZux33fS2iuTSfr4WsIUIV8Duxtmtm7tNsoC1euA83Ku3W6Zjbel3U2Yl2rv\nbD8j5d7e3z/cP+fJeLuoaieSSXoXAVIYkNQ90dZ4SF6C5PE3tTlDVNrEem9ngXbIFkj7RWdv\nHx2SKyCZA8ULeDLPIF8ASGFAariAF+gEEpKXIP14rp+LwfHLgOCK7sCdtXGkZ9kMg667dUBu\nglR7jZ/MYbSjGCClodduvw7IT5C8+vcfflOf63QBkjF0ka0pQqXLZj5Jz5UzIJV/aVTG3jUf\nGsUNkDI5jpQvINU/cWZB3+Xxk8npXdO1Q4ufaxeUrpLr2jpdH0yyuX8GQar78EujEbVMkFrE\nLkLLOTg3KHOaAGmFdmjtINWLVdj3NJ2uzIH0ZHfHGU639gFIuQpSqZzPpZaDfMP32ziL1GZr\nB+lNUUBtm34BWsZAeoWfucePOgQg5SpIH8nOx9Uq4MtLup8+13htUSsH6UY1YNhkujIG0tni\nzLfrEICUqyCpGS9kW9xmW49Uvuqe12l15AZIcsIbea9A1kDqKM5MdqoCSLkKktoMicyuay6Q\n3mcz+UeQ9Qm5AdJKWUKHmkxXxkCSo+NX6hCAlKsgbZHNZFX8u89eM/dt6p0tkEp78YSQ9yHk\nBkjybRSOJhwgeQCJqbErknoNQdU5Rieelz2Q1gQ2WKbsg/SITFczvB+pA27tmPICJO9iXlcj\nVKHdIurO2G8jOyAFN1im7IP0lkhWO10BWQOpsfeQAqQcBamYzboeHV9i3E/UXTPMbAhusEzZ\nBykm1nfcpUOy/TYKXJHyASTP2/H8xzpbzTf7O7jBMmUGpJoP9xjRRifIoRkFTodlpICzDdLV\nOqRlglSyxWj8+QpSXSPPt1N0SNZ67QIbLFMmQGpY0dlxJpLZsma6Dl7qXyeXklaVNZDkhtyP\n65CWCFLlTW2cgutIyvMVpD2v6iVAauMasr9ZcpBKXv/IOHWYcaT6j5/YS+1sgSRWBQ8kJ6Pp\nOjKGRy9tOl0ZA+k7fkmi+6y0RJBmiQdBnbH8BKl8hp+LSfFJ7HKbu9OJQxKQGpa191vghyQ6\nBEjfjfVPfB1pR1kCqV70uztPNp4uOUWonU559uba7Zl95tl30a+3QJC+k51MemFKfoJ0Kc/F\nOSqkk8jVeO2QDCTxW96D7AAT4h2yYpV79t8hWyZrclHj6WrG7u9WsYxCvdYlz5ea/yCzoSbA\n3CzMV7V3MpBkH9/dOuTYQXpNHKuNLvIsgXREDteQGe80XU/LEmqGAdlWAdJ2Wb5667q8BGmt\nzMZtKpUjrctCMpDq5ZfJa7ePHaT7A3/5mTLxjCR+PLrorf0Akpc9kOr5Kzecfk291iVPQFpn\ngeTF1lx3y/vUO9kVqbf4Mtl+/thBWiBTkv3NT6rYUFq315pIF27tuDIGUp1oRN314fMSJLVN\nm57bnMqk1RX8u53JIMyxg/Rgs12RvM8ndD/zLlreOTKzoVWApBbybIyH5CVIdeIBoQ3pL0gB\npHp2V9T7TRKdjzMbxP7nl5DaMrq/x/JosigomyB9b+0e0fJAeleC9Eo8xATJvfG0zlM+IwG5\nCdI2mY2XVMCOCzqfdj1910LycaQ9z71uFNmxgxTcYJkyAZLcFJOsJDEHZC93nPa3N8fMBm/j\ncKfdJXTSRQsE6aAccdHZNECqPotFdiC7NuUmSPIdEM4L0v6KLyYbTIohazMbAhssUwZAqpBF\nUNhEujzvxw+NhGQNJLHGpT8p4RYI0qHkID0kYifpkNwE6YBsRW9IW24cfJ/2zuJS84AGy5QB\nkKplTZKXyJrpOvL+qi8NO1sgiWu0s1yHtECQAm7t8uWNfW/IbKihILkdlzFzP2sg7dlkPJ5l\n69ZOvA7BIRM0jHR9OdSPvJSUf9ZAkqPjLXv294uyBT4WDzFAku/RPU2H5CZI8m3WzjxpyyHW\na7R3FkFaSjsPswfSd3zdz61NpKtqAC8RsrAkayD1FZVxkw5pgSC9Llug3kzdAElG36xDchMk\n9VINtYvQrfZ1thWA5BXfOeXqN5pK13pRIgW6xLMG0mJxajKs1wJB2iZb4OZ4iNlrx4fLh5Ok\n5iZI9eL3tptKTNUIZt5IvFsBSLm61Lx2Er3rZmqBINXzzQ2cIU3ObHh33qxnaFJyEyTvK7Z3\nT6f39Jmeu+bmd6h3awfpVcFRkjmAmev+bnhj4d1f0OgWCJL3JOvsKXhIB+TlgKy3mY/IvkCi\nm21fu9wE6WvZbaQrMylIscfHDpy+gwSkcWZDzfJRg66jw0otAaRqsYqlq056XoJ0WDzQdo4X\n+b4bhoxcZi6BafEgbT6vyxlL6Llouu6Wt3Z6BW1SkGZZN/whQdpDF+Pz9/12Jkt5WwJIakM4\n/e5gG6SSfHgZs5rErlaD/MAXZZ5DTt7yQdrES2A8ySZN1wxZQm80mS4K0vvCeYCu+jAg3d/R\ncfpsUZbsYb1Ax7cEkNQ4kl65Y4L0/eUd2ozcRAJyEyR7ZsMUYTbP2yiaCaQ+Is9rGk+X7DpL\nMiudgrRceutJViFAEusm26nly9eJQ3fQkLYEkIrlu0T3xUMMkKJn8li983qOglTRxrxxkXs2\nnKW9WzxI5bLtT208XV+K2G66zL5bs6XJF409IA+mg0KA1Fkc63xpzhFmZ+3QEkCSk4BI36QB\n0n0i0+N0SG6CVCznx2yXtpNQWS0epEMyz6ObSNciHhuf5V/DnoLOot0JFKRt4lgjdUgIkGTC\n1AYackSL7GDcIkA6yN5bPOgHHWCAJDYwddrpkNwEaYOsLLU2T3JFyrTFg1QTAFLDU8N6jtfz\n+MV14bSmXsZcyH+HyNy8ECDJyjhTJeRKZvUmU/NbAkgN43gmRzTxMmb5apu2OiQ3QVolW5Ga\nIiTvJiZq7xYPUomTcBUx0vVOVz9yiFqwVSVb91+0gzmO9NZVkxaSV4OlYe/v+E409cuG9JtO\n67IlgKTm1sT7VEyQzssTkORyuvjU54nC/LP2bvEgFcsimNB4uorFb8tYacpHJucS4pHhTfTj\n93J38gsnOVxLAOkvskD1Q5IB0q3mVdnLVZBkd228m26wMI15ki0cpHrZbbSs8XSpKULykvSV\nNMn8+Ey/1uUKaW42bx68lgWS3qvaAOkL8WuyUofkCkgNL00/b1H8PvsJmQ21v7Ssu8u0f4sH\nybuDZ7k7KVKarktkCcnehlrZzfms9sgYSF3NK9I8YfbQDi0BJLWP1aPxEHMcaQ0b2byZtMFc\nAYk/LHfeJa3HZDaul/ZoYd6m/Vs+SEdYCx3wSRPpkjfp8Qnxcl9W4p4xkOQDq1qPNFuY7VrW\nONI7snyb3CCyZM0TdF/2XAFJ3h+cI031qKd+YEUvXlfSGdnyQfJeG1LQ5QZaoo3NbNgqzIPS\nfFB7ZAykkeJU90jzYWGeqx1aAkg/ygL9Nh6SH3PtVLtQGeXLJpw+8Yw91d1xhtDdvFs+SOLH\ng+5VT9N1mywwOQt7rzTJRJ2MgSRvD+6XZtUQbpLKaQkgeUt4rsiTnwVS/eebjVwmBym2bYuR\n7oyBNEY2BNVDWzHeN4bu1w517283yGnxIDXIVcGrdTRN1y0mSGqO5SDtken3I81U9oGZnduO\notPOWgRIRx4+3el9P0maCdLHZ/l3SE+QgKQgbRrgOD3pWoaMgXSldUXyT7XRKJPiV941JiC3\neJDUFKH5jadLPSPJBqz2fB+sPTIGknwcoztC729565H8TO9v+o19+8X7P8m7WJOBtFs8VpJm\nlDGQ3jefkVjsJvJE5C3v4N/ovUECWjxIambDRY2na4SMlj+KatSJtO6MgSQ3/jDeaNAiQUry\n6svbRRkM1yHJQJorvPV8gvJVy16l1ZHGXjteO5126YCXnQe0sdqxo1s8SOq1LmR7E5quq2W0\nnI2oZjZko7NB1faKZgAAIABJREFUTNhsS+YbZQakdXOZurbnH6rbKUdAks/0HXRIMpAuEN59\nlb2ZXdSHkQeXNIK0lo1wjSUOBkhy19FbdEiLB+mIHBla3Hi65EITNUdFdTYQ74yBNKCRysgE\nSHKASugqGZg9kPbdceVS+qpGAyT5iHqUMxuuEd5qtle52KCf7C6ZPpC+E5ulke1NDJDs6V2t\nAKTDculIEzutviAbmOydUb21ZEKRNddu5vmL0jTXrqM4FZnunSmQXtsptTn7IG1i2ezwhg4w\nQHoiobiTgSSXM6v5BGrPPP3GnvSBJF9D1F6XkgGSvHHpqUOSglR655Qr1tG6zUOQVGdDwBv7\n5MI+uRcK3bHQAGkpi+xM3sobAiR5e0BeX5spkOLp/THrINWKq0YP3TIMkOQirD46JBlIsitt\nmDQfl5W1Pe6QPpDUsIjOmQGSjCXLP5KBdOA05kweLvIRpAb5lqenG0/XRvnLI9OiXijVBEjb\nzHsLLxRI4lzd9NpRr/xgiwPpQ1mgTezZcJWI7ahDkoEkd9xWK7jEJgJOW10s6QNJvoCut85J\nYyAV6JBkIF0mvMl7HPIQJO8ZnokzSNXTdMXEyJuaUxmVJUQWmmRshaz3SBfHGawHYA9e2639\n+A9IfEsASV3in4mHhFghK/cFuFjFTeam8YaTdIEkh8fJnMtjB6lBPlGR/WTzESTRMdSGlLCR\nLnHBUu1LvXWAvGYgY3s2eEv9x7fu8Z/qatH5QGb5tQSQ5Lpf56l4iLlnw+k89iMdkgykIl5Z\nHeP9nMWz2jgdlxlvOElbr93eaX7lPEoCGgOpvQ5J9g5Z2d91vY62QDq4xSjv3AQp8RrTyDNS\ngWwKqrOhie7vtO4iJF5i2OY7acof5yHaoSWApBbyvB4PMUAqFa91INs2J53ZsGta+zZjCXVe\n8WfG9II0grRrvI/sCnKr3VhnQ28dkuzWTk5PJlvuGyAV+7/1beaTjOQkSGrebtfG03WFjJaz\nvxvEFd3Zpj0ytq9dJ5NwOYe1IO2zv5sVpArRadpGF7kBknymJzOyAiatugcMM2MzGyrEjpDk\nkmSAJJfATNMhya5IBUmvSPVieGyODslJkL6TpJANX2i6rpXRain0Vn4/S9aZmCAdeWzMGZdv\nJwHhNz/pJ0256NJpWSCp4tfbyRggnSV/PXRIjsz+lm9A69hEZ4Oc3kWmyxzFFYm8EYWCpF6z\nq0dVchKkWplMMnuOpusz8Wuhu412Tuoz/El6MHMc6fsHbn2BNsEQIMk7ZzUYKbt2yCB/SwBJ\nTV5sYj2SHJR2dEiOgCTfqkW6lRobkNXPC18vX/QaJckASW5ZSDqSKEirHTs6J0FSU4RmN5Gu\nuYykNvFH/h/ZhaHjOuJggLSaleBZh3RACJDkSPEIaYqXRtOJDi0BpM9k8etZ7QZI8n72qDc/\neXPudWtoe80YSBNkunUZGyDJuuuvbP68O9bYb4OAVM62JItv5cVEQVIbq+iJezkJUkxeV8m2\nAGa6NvV3xuvpWmKoojMZ3KEg7RWzES7WIeFv7eKDkQ+z3SUmk2bUEkBSe/020dkgNlo92lu7\nBv6IOo44ZAykO0XC2ul8J+ts2CpMY78NOrPh8PM33PYpPRUFqUZclifoe/qcBElOGe5A9otL\nkq5SWe/kIZOC9GdZ77pFhwdJ94LsXrH0HToi2xJAelDmUj91GiCdLqN1SDKQ5E0QGTjKGEjy\nlpRMAmwMJDVuv8iuypTm2u1gPyfnkN/uJkGq3sU0x3mWf8rAHHmHrAnS907CbwsFSb27Ql/B\nwm8QOVCHtMApQmrhpNoryftmRv9hd8S/3i0lkC4XzmSEIGMgLROnaqMTkwwkuSKmjS6llCat\n1rz8wJu0gJsESe4kISUbS6681dwAaZ9MI1mPtI9M039ZxPYgL87ZZVZd6t3fZFV70XctDqRZ\nskAvlPZOfnM8VjXo9imBJKcI9dMhGQNJvVxBF3ljIHWR5kphkmVVJkhbJrQ/bS5NizUgW7Xr\n6GY2bHZGzlHqnWWQKmSJNLGMwmscpPjMhq1jCtqMi48qHREb8MYnjtQ/3NPpNJ/mOvVeu7OV\nvefits6Q14l3AEg7PzM6XHMTJLlyL74eQczqiU90aJsSSPJgZNPBjIEkJ10O0CGNzWxQnSRV\nZ3CTvAvTAEl0cI8gSTVAqlrU2enxAElaEpD09ozjswySaq+kNywJSPVi6XN8qF0sbu4Sf4/e\n9j7+E9Ll8XYipgxdTK4jx/6MJN9wQjZtSArS1uH+s+6LJCA3Qdotc6l2V5f9xtea5lGCVM5n\nUXf4VodkDKRqcb+wRIckA6lSgLRROxggyb7Jx3WIAZKYxEae/HISJNX93cQUIc8E6bDcl1UN\ne8gFtOpOr1bspKI2/olKbzLTIXWQ1BDWCmGO0A7JQNonni7024FzFCR1id8pbbnjixrGl1Pz\nj7LXbq9o3Xof8cyB9JxIWF/9G9kYSNat3TDtYMxskN5kH2wK0jYRSyZ/5CRIB6w8e0lBUj+g\natdGOWCoHm8flXmWjXCH9H5EHyx1kLpJc7psU0c3s2Gh8CYr4nITJPUaBzV5Ua6bUBtVyO7v\no7wiybW+k3WImemG91e8YNz+hn9G0j2MjT0jqX0wAjobrJr2TJBUEenfh8cun2dsmpkTIKm5\ndm0aSZcQBUmhoUaKxJxKp5c0h8po+fuqRhvJjKLUe+3U3KVhEiTtkAwk+WIhskQzN0GS217G\nb1xEv2db1U6mithO+sup7NlgZTrKOmh7vk2+fewgyXn+7fThG7siqWkoybu/6yxvzwTpXhmt\nEu72ZM2ArPfMDZDUuDFpoElAUutpVTbkezPVCLacYuW8KUz1it779cGO/dbuDGkf3RVJzjoh\nNxO5CZKc0x4fT5C5VM8eS4V5uv5yMpBkFyC5+zUyLTZ97k5HDI8ZpJ2iG4TvA3D4CaYbnUv5\nJz+kzJVaIfupmUmv8SsSWU9LQVIb9KsHBDnpkkxyzwmQ1KxJMgslCUhRaxchOalS9aypiaVy\nCqba4JjsqJU6SKp4h6YE0gdmOr1cBekOmSv1UCS7ftSy69SekcYL7146hGa6Sh77MR197CDt\nIiCp1Z6k7mUzib/xgM9xbWqKkHpGauKKpN5XLdfTqI2sGnsPUXOCpFYYkW3dkoCkdhFaKG05\nv6ibNOUFv0DVnniuGUgKMHWQ1D3nXPNUXnKQ5IgW2dIlN0FSWxhNl/ZAYap5Z6l1f3dIwI5m\ner88Fn2BT9hbu7bs8FFnxItKUwVIcvte9ZYX70Zm9SNzMClIR2TCyG85BemgIEfNRtopvck+\nFjkBknqHLNmFIQlIqmtCPSO1MRv7h9YPkVj/OZccLHWQVPFKkIz77KZBkg/tZ+iQ3ARJrSlW\nSwjEwv+uaj5Mm5RAapfgTTN9WPYIki2Njx2k8+WpWGdDlCyXuFWAJN5W00E96snnB7IhVGNX\nJLIzBQVJzjtT93JF0iTzN3ICJHX71V9HJwFJdR+o6QYWSDfLaFk/R+TAPOliMUAqX9iv0wS6\nC0NjnQ3qQTtxtkwykGTXBLlbyE2Q1KTV+MYf9/qXlQHx8YKgcaTN53Xqtyie7UZA2ksyLQYQ\nhpGHk2MHSfYyOaypNAKS91BH/8ku3q8xX9YGuS3fmwgSmZFBQZLzNdRzeYM0yczonACpQqar\nWyPpEqIgfSu9R0nburVTGxx/Lky15f4V+mAUpJiYi09GmQyQZEfGAmmqVqIbofuy0ZwNkM7K\nE5DkpmNkQmHZBvJCCVkGTT0jiYXqE9TJ7Vu7yoVdnL6Pxk9Wf4/vcAHdjPLYQZLztzg2jYHk\nlfWepMtb7irWRiWl7t4eTs/lKl6BRN7YQ0GaJqOXy1RIs7EFdM0J0jaZLrJPRTxdH3Zkauu0\n558sRG0xoG7ezjQzpXrW5BrZBdIkt40UJLn55Fk6xABpG7/cnabapJp2pirjR7bq/RzSEgyQ\npghn8uSXoyBVsF+Tc0k2Kt/+VB/stOQgyZ8L9SYR60awQayFVO919epX+L97l5KpkSFAkrcL\nDnvsaRSk+vh7h309K5zj/QPzjZ9ItdR8nP4CBUkNWckuKzWUSfaDyAmQdsl0NbbUfLPT+xyl\nTjxdata/+qXvYZJymgmS/CGizzUUJPmmYfJqEHMXoY/Oc9rOjnfWyo1X47124nmW/JQbIA03\n0+k1J0iHXtxgTCiw9v5eRV/+7T3oXzUGxbt21Q+/jjcmHMtYNVHPMb3lDUF7dXIxv+AcUgzJ\nQfrq+Q8Mm4KkTsVm/QSDVCRuJ1Qfquqy2qNchcboL1CQ1shouWCpUppkH4ucAEn9tkzXIUnS\n9Z7Mhboiyal3atxTNXZ5xy/3taWrVihIco5lW91kTZC8Wuc8bVhXJLWPlZ4EZICU2N3VbCDd\n7ae8x0skwAJptfMXbYipNx3VFibJOxtUd5f6NSkwveU8E/Wzpjob1uqDJQOpgi3KGE42zW0U\nJDbdIBgkWdOqX/51+eXXhKmeesjoOQVJ7jGgrrtqSdxoko1mAqn86SUv6NoQQ4LkpztZur6R\nuVBdJrJ1q2+rmpSTl+VWnxRSCpJcPH5pPKBm9ZKn6SwqAySFhiweOQeIvA7cAElVtA5JJ0if\n3nPfF9ROBpJYbdfhcx2SDCT50KnGkQoSskFBcmWs+lmzsFNd63JCrOpxXaAPlgwkMXw7iA5d\nEJDUqVjRBYPUX3rLUpJ3emqVgPo9IJNrKEhqcaPs4FLdzM0P0kes/+sM3ZO2oaNTMI46JEnX\nGzIX6tlDmuoeXtW7/Jra2WOKOsiR20acq9e07xEY3qTsnay8e2/VCTFAUh1YsnjUK+P09pwZ\nBKnqsTl3fxe3Gq5nR16oo7++c87TtC/NAEl2wNykQ5KBJJOtfpyTjyOpCcenmV9W3mpfBdnf\nrebHDtUHSwJSsaxLvStLo1ckthllMEgKOwmS2t1fXqbVFKEmQJJbe6njqRd6ka6J5gGpUiSs\nv67Mb/XAWVC61G9JAEjy+fYeaarb2Qp+cxEfAJBjKJ1kSurFc01/fXdngNTFBGmmNPXvqwFS\n4k95CJD2sB/FDvHxlyfFoeNrNB5jTwBn6Jk3B5Zeeot+q1PiixmOAiT1VJkcJPVTPsT8svKW\no6Lqoq0mg9GhdwOkwh4dzvhYGV9Jb/UubO/wU1deszaecFW+a7xEkNYs93Wvczr7WP4hTZis\nWjUypH5TpdnEgKyadzZVmOoy3Nh4TVZBekYmRO+kZoJUt3LKpOVVTaRLPSaOk6FW1alfHllC\ndzpmIzpXmGqAVg6aOrJFqwmxfPThkVt8zXP6so9bePe7eu6WxaP6NeK9DYcWjb90dbyirYR5\noUASU286qVFSsXox3nrktLP4a4g+5il9vqmU1K++ZPxtop1U8Nxd4JzHP3mjlg1UvVIy4ffg\no5ljZsfvEtXcHHVrZ51KlZi8GKqpNt3U10un9ug+VaMk5nepRUFfS2/1StQafmWdqgpYnWqz\nlwjSZIfobuotT6ZGc+U0ddXZEO+bPPLEtIl3xn8V1ZDV+cJUvWONdTM3BtKeuWOnk+35hdIB\n0kUyIfx3av4MX9OcfuxjBp+nXjeKRZ4ZbSJdIlcFamMJq+rUrH/5rKxu0tUSDdks1Ow5decs\nm6y6EeTvxVC3JVz3NXIq1fegehv38AHb+KtBLG+vjiU8vthWzO/sViZTmQDSkWu7teuzSoWq\nMWu1nd8gYap7CznaWCBv52KiEDqpK5SdEj5tqtNeemCh3aSIhjbxZXExlNveej9Y0ZapLmey\n11mhoebWlPIibKd++2XXhGrNX0pvNX1WTuBWF09V/KwrLRGkt96VWmGCJH/KZBeVujaqWzuV\n7vqxPFLRoW7tZHnLJ+tGJ4c20mA/5aVAdzRlShWkisXjRs05aIZdKhPCp2SrtszFu0Xk/dac\nJtJVzO6wCh5SoVYRyF+LbtJUP01tG/dW1y/5El9158yLfoKz43Opx02Q5G28emRSPUFy/Pv1\nxk8lG2h87tIUEtsISAKV5Wau4pTKUVJ1Q6U2cZQPUeqeaE3jKXmVfPmgc4HK5OeXC5CaKCJp\nHhK57i6Zfcvytkw1hC2f0tVcfPXTI9elqotfXxktlyCrOSzq50LeWasO2FEymj31JIIUv/a/\nb4JUaxxLpSQ+6VV+6WHzzKoM5OoQNY4Uf6L68bq+PWd8y/9NbLAN8rKs77+4UgVp7szd+xZN\nqzfDZEL4avH+vQ8qrRQgdSHJtNM1a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          },
          "metadata": {
            "image/png": {
              "width": 420,
              "height": 420
            }
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "This boxplot highlights the variability in counts across locations, underlying the importance of including random effects in our model to account for such variability.\n",
        "\n",
        "## Conclusion\n",
        "This tutorial demonstrates how to fit and interpret negative binomial and Tweedie mixed-effect models using the glmmTMB package in R, addressing overdispersion and the flexibility to model various data distributions. The plots provide insights into the data structure and the rationale behind choosing mixed-effect models for complex data analysis."
      ],
      "metadata": {
        "id": "AxHS5KV9_tXI"
      }
    }
  ]
}