maxlikmtKernelDensity#
Purpose#
To compute kernel density estimate and plot for a given dataset using specified kernel types and parameters.
Format#
- out = maxlikmtKernelDensity(dataset, c0)#
- Parameters:
dataset (string) – Name of the GAUSS dataset.
c0 – Instance of
maxlikmtKernelDensityControl
structure with detailed configuration.
- Returns:
out – An instance of the
maxlikmtKernelDensityResults
structure.
Example#
new;
library maxlikmt;
// Specify the dataset
dataset = getGAUSSHome("pkgs/maxlikmt/examples/maxlikmttobit.dat");
// Initialize the control structure with default settings
struct maxlikmtKernelDensityControl c0;
c0 = mlmtKernelDensityControlCreate();
// Customize the control structure
c0.varNames = "Y";
c0.Kernel = 1; // Use normal kernel
c0.NumPoints = 100;
c0.EndPoints = {-3 3};
c0.Smoothing = 0; // Let the function compute the smoothing coefficient
// Compute the kernel density estimate and plot
struct maxlikmtKernelDensityResults out;
out = maxlikmtKernelDensity(dataset, c0);
Remarks#
The function generates kernel density plots of the selected parameters using the specified configurations. This method is useful for visualizing the distribution of parameters or data points within a dataset.