mcp

Bernoulli family for mcp

Checks if all terms are in the data

Compute information criteria for model comparison

Cumulative pasting of character columns

A change point in a time series

Two change points between three binomial segments

Two change points between three linear segments

Example fit of the ex_demo dataset

A change point between two plateaus

A change point from plateau to quadratic

Two change points between three linear segments

A change point between two trigonometric segments

Two change points between three heteroskedastic segments

One change point varying by participant

Exponential family for mcp

Expected Values from the Posterior Predictive Distribution

Format code with one or multiple terms

Density geom for plot.mcpfit()

Return a geom_line representing the quantiles

Call get_formula_str for multiple ytypes and paste strings

Gets code for ARMA terms, resulting in a "resid_"

Extracts the order from ARMA parameter name(s)

Compute the density at a specific point.

Get a list of x-coordinates to evaluate fit$simulate at

Build an R formula (as string) given a segment table (ST)

Adds helper variables for use in run_jags

Make JAGS code for Multiple Change Point model

pp_check for loo statistics

Get priors for all parameters in a segment table.

Get JAGS code for a prior

Expand samples with quantiles

Build a table describing a list of segments

Turn formula_str into a proper R function

Internal function for summary.mcpfit, fixef.mcpfit, and ranef.mcpfit

Get formula inside a wrapper

Test hypotheses on mcp objects.

Inverse logit function

Inverse probit function

Checks if argument is an mcpfit object

Logit function

Internal function to get samples.

Fit Multiple Linear Segments And Their Change Points

Regression with Multiple Change Points

Add A family object to store link functions between R and JAGS.

Class mcpfit of models fitted with the mcp package

Plot full fits

Plot individual parameters

Posterior Predictive Checks For Mcpfit Objects

Fits and predictions from samples and newdata

Samples from the Posterior Predictive Distribution

Print mcpprior

Probit function

Recover the levels of varying effects in mcmc.list

Remove varying or population terms from a formula

Compute Residuals From Mcpfit Objects

Run parallel MCMC sampling using JAGS.

Transform a prior from SD to precision.

Summarise mcpfit objects

Get tidy samples with or without varying effects

Convert from tidy to matrix

Takes any formula-like input and returns a formula

Unpack arma order and formula

Takes a cp formula (as a string) and returns its properties

Get the intercept of a formula

Unpack right-hand side

Unpack the slope of a formula

Unpacks a single term

Takes a formula and returns a string representation of y, cp, and rhs

Get relevant info about varying parameters

Unpack varying effects

Unpacks y variable name

Add loo if not already present