f.lik.con: Calculate likelihood for continuous response

Description Usage Arguments Value

Description

Calculate likelihood for continuous response

Usage

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f.lik.con(theta, x, y, dtype, fct1, fct2, fct3, model.ans, mn.log, sd2.log, nn,
  Vdetlim, CES, twice = TRUE, ttt = 0, fct4 = 1, fct5 = 1,
  cens.up = NA, lb = -Inf, ub = Inf, par.tmp, increase = increase,
  x.mn = NA, track = FALSE)

Arguments

theta

numeric vector, the initial regression parameter values

x

numeric vector, the dose values

y

numeric vector, the response values

dtype

integer, determines the type of response

fct1

numeric, value for parameter a

fct2

numeric, value for parameter b

fct3

numeric, value for parameter var

model.ans

integer, determines the model that will be fitted

mn.log

numeric vector, transformation of the response values, see f.execute()

sd2.log

numeric vector, transformation of the sd of the response values, see f.execute()

nn

numeric vector, the number of responses per dose level, for continuous summary data

Vdetlim

numeric vector, values of detection limit

CES

numeric, value for the CES

twice

boolean, if some parameter values are equal, see f.execute()

ttt

numeric, time variable

fct4

numeric, value for parameter c

fct5

numeric, value for parameter d

cens.up

numeric, value for right censoring

lb

numeric vector, determines the lower bound for theta; default value is -Inf

ub

numeric vector, determines the upper bound for theta; default value is Inf

par.tmp

numeric vector, regression parameter values, see f.pars()

increase

boolean, whether the response values are increasing or decreasing for increasing dose values

x.mn

numeric value, the mean of dose values, see f.execute()

track

logical, if TRUE (FALSE by default) print the name of the function which is currently being run

Value

numeric value, minus the sum of the scores (total likelihood)


alfcrisci/bmdModeling documentation built on May 28, 2019, 12:32 a.m.