hessian2: Hessian With Small Sample Correction.

Description

Extract the hessian from a latent variable model, with small sample correction

Usage

hessian2(object, indiv, cluster, as.lava, ...)
# S3 method for lvmfit
hessian2(
  object,
  indiv = FALSE,
  cluster = NULL,
  as.lava = TRUE,
  ssc = lava.options()$ssc,
  ...
)
# S3 method for lvmfit2
hessian2(object, indiv = FALSE, cluster = NULL, as.lava = TRUE, ...)

Value

An array containing the second derivative of the likelihood relative to each sample (dim 3) and each pair of model coefficients (dim 1,2).

Arguments

object: a lvmfit or lvmfit2 object (i.e. output of lava::estimate or lavaSearch2::estimate2).
indiv: [logical] If TRUE, the hessian relative to each observation is returned. Otherwise the total hessian is returned.
cluster: [integer vector] the grouping variable relative to which the observations are iid.
as.lava: [logical] if TRUE, uses the same names as when using stats::coef.
...: additional argument passed to estimate2 when using a lvmfit object.
ssc: [character] method used to correct the small sample bias of the variance coefficients: no correction ("none"/FALSE/NA), correct the first order bias in the residual variance ("residual"), or correct the first order bias in the estimated coefficients "cox"). Only relevant when using a lvmfit object.

Details

When argument object is a lvmfit object, the method first calls estimate2 and then extract the hessian.

Examples

Run this code

#### simulate data ####
n <- 5e1
p <- 3
X.name <- paste0("X",1:p)
link.lvm <- paste0("Y~",X.name)
formula.lvm <- as.formula(paste0("Y~",paste0(X.name,collapse="+")))

m <- lvm(formula.lvm)
distribution(m,~Id) <- Sequence.lvm(0)
set.seed(10)
d <- lava::sim(m,n)

#### latent variable models ####
e.lvm <- estimate(lvm(formula.lvm),data=d)
hessian2(e.lvm)

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