bootstrapEMBatMix: Bootstrap the Batschelet mixture parameters

In keesmulder/flexcircmix: Fit Mixtures of Flexible Circular Distributions

Description

Bootstrap the Batschelet mixture parameters

Usage

bootstrapEMBatMix(x, B = 500, parallel = TRUE, verbose = FALSE,
  bat_type = "power", n_comp = 4, init_pmat = matrix(NA, n_comp, 4),
  fixed_pmat = matrix(NA, n_comp, 4), ll_tol = 0.1, max_its = 50,
  optimization_its = 10)

Arguments

x	Numeric; A set angles in radians.
B	Integer; The number of bootstrap samples.
parallel	Logical; Whether to perform bootstraps in parallel.
verbose	Logical; Whether to print debug info.
bat_type	Either 'inverse' or 'power', the type of distribution to fit. The two distributions are similar, but the power Batschelet distribution is computationally much less demanding.
n_comp	Integer; Fixed number of components to estimate.
init_pmat	A numeric matrix with n_comp rows and four columns, corresponding to μ, κ, λ, α, in that order. Gives starting values for the parameters. If any element is NA, it will be given a default starting value. For mu, the default starting values are equally spaced on the circle. For κ, the default starting value is 5. For λ, the default starting value is 0, which corresponds to the von Mises distribution. For α, the default starting value is 1/n_comp.
fixed_pmat	A numeric matrix with n_comp rows and four columns, corresponding to μ, κ, λ, α, in that order. Any element that is not NA in this matrix will be held constant at the given value and not sampled.
ll_tol	The likelihood tolerance for the EM-algorithm.
max_its	The maximum number of E-M iterations for the EM-algorithm.
optimization_its	The maximum number of maximization iterations within the EM-algorithm.

Value

A matrix of sampled bootstrap values.

Examples

x <- rinvbatmix(100)

 bootstrapEMBatMix(x, B = 5, parallel = FALSE)

keesmulder/flexcircmix documentation built on May 29, 2019, 3:02 a.m.