bootstrap_lm_basic_cont: Parametric bootstrap for the basic LM model for continuous...

In LMest: Generalized Latent Markov Models

Parametric bootstrap for the basic LM model for continuous outcomes

Description

Function that performs bootstrap parametric resampling to compute standard errors for the parameter estimates.

The function is no longer maintained. Please look at bootstrap function.

Usage

bootstrap_lm_basic_cont(piv, Pi, Mu, Si, n, B = 100, start = 0, mod = 0, tol = 10^-6)

Arguments

piv	initial probability vector
Pi	probability transition matrices (k x k x TT)
Mu	matrix of conditional means for the response variables (r x k)
Si	var-cov matrix common to all states (r x r)
n	sample size
B	number of bootstrap samples
start	type of starting values (0 = deterministic, 1 = random)
mod	model on the transition probabilities (0 for time-heter., 1 for time-homog., from 2 to (TT-1) partial homog. of that order)
tol	tolerance level for convergence

Value

mMu	average of bootstrap estimates of the conditional means of the response variables
mSi	average of bootstrap estimates of the var-cov matrix
mpiv	average of bootstrap estimates of the initial probability vector
mPi	average of bootstrap estimates of the transition probability matrices
seMu	standard errors for the conditional means of the response variables
seSi	standard errors for the var-cov matrix
sepiv	standard errors for the initial probability vector
sePi	standard errors for the transition probability matrices

Author(s)

Francesco Bartolucci, Silvia Pandolfi, University of Perugia (IT), http://www.stat.unipg.it/bartolucci

Examples

## Not run: 
# Example based on multivariate longitudinal continuous data

data(data_long_cont)
res <- long2matrices(data_long_cont$id, X = cbind(data_long_cont$X1, data_long_cont$X2),
      Y = cbind(data_long_cont$Y1, data_long_cont$Y2,data_long_cont$Y3))
Y <- res$YY
n <- dim(Y)[1]

# fit of the Basic LM model for continuous outcomes
k <- 3
out1 <- est_lm_basic_cont(Y, k, mod = 1)
out2 <- bootstrap_lm_basic_cont(out1$piv, out1$Pi, out1$Mu, out1$Si, n, mod = 1, B = 1000)

## End(Not run)

LMest documentation built on Aug. 27, 2023, 5:06 p.m.