logLik.nmm: Log-likelihood(LL) with supplied coefficients.

In nmm: Nonlinear Multivariate Models

Description

Log-likelihood(LL) with supplied coefficients.

Usage

## S3 method for class 'nmm'
logLik(
  object,
  new_coef = NULL,
  separatenmm = FALSE,
  transform = FALSE,
  methodopt = "NA",
  ...
)

Arguments

object	Object of class nmm.
new_coef	"New" coefficients for which LL should be calculated.
separatenmm	if TRUE, returns separate LL for each equation.
transform	if TRUE, do quantile transformation (normal quantiles).
methodopt	"NA" means that automatic algorithm was used in maxLik, if equal to "BHHH" will return LL for each individual.
...	some methods for this generic function require additional arguments.

Value

Returns log-likelihood.

Examples

#example  continuous nonlinear
library(systemfit)
data( ppine , package="systemfit")
hg.formula <- hg ~ exp( h0 + h1*log(tht) + h2*tht^2 + h3*elev)
dg.formula <- dg ~ exp( d0 + d1*log(dbh) + d2*hg + d3*cr)
labels <- list( "height.growth", "diameter.growth" )
model <- list( hg.formula, dg.formula )
start.values <- c(h0=-0.5, h1=0.5, h2=-0.001, h3=0.0001,
                  d0=-0.5, d1=0.009, d2=0.25, d3=0.005)
model.sur <- nlsystemfit( "SUR", model, start.values, data=ppine, eqnlabels=labels )
eq_c <- as.character(c(hg.formula, dg.formula))
parl <- c(paste0("h", 0:3),paste0("d", 0:3))
res <- nmm(ppine, eq_c=eq_c, start_v=start.values, par_c=parl, eq_type = "cont",
 best_method = FALSE)
logLik(res)
logLik(res, new_coef=res$estimate)
logLik(res, new_coef=model.sur$b)
#example discrete
library(mlogit)
data("Fishing", package = "mlogit")
Fish <- mlogit.data(Fishing, varying = c(2:9), shape = "wide", choice = "mode")
## a pure "conditional" model
mres <- summary(mlogit(mode ~ price + catch, data = Fish))
data <- prepare_data(Fish %>% data.frame %>% dplyr::select(-idx),
choice="alt", dummy="mode", PeID="chid", mode_spec_var = c("price", "catch"),
type="long")
eq_d <- c("a1 + p1 * price_1 + p2 * catch_2", "a2 + p1 * price_2 + p2 * catch_2",
             "a3 + p1 * price_3 + p2 * catch_3", "a4 + p1 * price_4 + p2 * catch_4")
par_d <- c(paste0("a", 1:4), paste0("p", 1:2))
res <- nmm(data, eq_d=eq_d,  eq_type="disc", fixed_term=FALSE, par_d=par_d,
best_method=FALSE)
logLik(res)
logLik(res, new_coef=res$estimate)
logLik(res, new_coef=mres$coefficients)

nmm documentation built on Jan. 7, 2021, 5:10 p.m.