mssm-Laplace {mssm} | R Documentation |
Function returned from mssm
which can be used to perform
parameter estimation with a Laplace approximation.
cfix |
starting values for coefficient for the fixed effects. |
disp |
starting value for additional parameters for the family (e.g., a dispersion parameter). |
F. |
starting values for matrix in the transition density of the state vector. |
Q |
starting values for covariance matrix in the transition density of the state vector. |
Q0 |
un-used. |
mu0 |
un-used. |
trace |
integer controlling whether information should be printed during parameter estimation. Zero yields no information. |
An object of class mssmLaplace
with the following elements
F. |
estimate of |
Q |
estimate of |
cfix |
estimate of |
logLik |
approximate log-likelihood at estimates. |
n_it |
number of Laplace approximations. |
code |
returned code from |
disp |
estimated dispersion parameter. |
Remaining elements are the same as returned by mssm
.
mssm
.
if(require(Ecdat)){ # load data and fit glm to get starting values data("Gasoline", package = "Ecdat") glm_fit <- glm(lgaspcar ~ factor(country) + lincomep + lrpmg + lcarpcap, Gamma("log"), Gasoline) # get object to perform estimation library(mssm) ll_func <- mssm( fixed = formula(glm_fit), random = ~ 1, family = Gamma("log"), data = Gasoline, ti = year, control = mssm_control( N_part = 1000L, n_threads = 1L)) # fit model with time-varying intercept with Laplace approximation disp <- summary(glm_fit)$dispersion laplace <- ll_func$Laplace( cfix = coef(glm_fit), disp = disp, F. = diag(.5, 1), Q = diag(1)) print(laplace) }