{ "cells": [ { "cell_type": "markdown", "id": "f569a665-f294-4842-9ff6-d602efc63e40", "metadata": {}, "source": [ "# Log Gaussian" ] }, { "cell_type": "markdown", "id": "6b9201df-6507-46df-96e2-a6580f9bf43b", "metadata": {}, "source": [ "`lamatrix` provides a log Gaussian to fit to data. This model has some nuances, let's take a look." ] }, { "cell_type": "markdown", "id": "bfba5521-cf4f-4b81-9733-945b3e0e2250", "metadata": {}, "source": [ "Let's look at the equation for this model" ] }, { "cell_type": "code", "execution_count": 1, "id": "47e00fe5-dd14-4dbb-ab90-4df8c172f663", "metadata": {}, "outputs": [], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "x = np.arange(-10, 10, 0.01)\n", "\n", "\n", "from lamatrix import lnGaussian, Gaussian" ] }, { "cell_type": "code", "execution_count": 2, "id": "6d10c015-e724-465d-bbdf-c3db1b0e3581", "metadata": {}, "outputs": [ { "data": { "text/html": [ "