reltest_predict: Make prediction from one model

In fitdistcp: Distribution Fitting with Calibrating Priors for Commonly Used Distributions

Make prediction from one model

Description

Make prediction from one model

Usage

reltest_predict(
  model,
  xx,
  tt,
  tt1,
  tt2,
  tt3,
  n0,
  n10,
  n20,
  n30,
  pp,
  params,
  dmgs = TRUE,
  debug = FALSE,
  aderivs = TRUE,
  unbiasedv = FALSE,
  pwm = FALSE,
  minxi = -10,
  maxxi = 10
)

Arguments

model	which distribution to test. Possibles values are "exp", "pareto_k2", "halfnorm", "unif", "norm", "norm_dmgs", "gnorm_k3", "lnorm", "lnorm_dmgs", "logis", "lst_k3", "cauchy", "gumbel", "frechet_k1", "weibull", "gev_k3", "exp_p1", "pareto_p1k2", "norm_p1", "lnorm_p1", "logis_p1", "lst_p1k3", "cauchy_p1", "gumbel_p1", "frechet_p2k1", "weibull_p2", "exp_p1k4", "norm_p12", "lst_p12k3", "gamma", "invgamma", "invgauss", "gev", "gpd_k1", "gev_p1". "gev_p12". "gev_p123".
xx	training data
tt	predictor vector
tt1	predictor vector 1
tt2	predictor vector 2
tt3	predictor vector 3
n0	index for predictor vector
n10	index for predictor vector 1
n20	index for predictor vector 2
n30	index for predictor vector 2
pp	probabilites at which to make quantile predictions
params	model parameters
dmgs	flag for whether to run dmgs calculations or not
debug	flag for turning debug messages on
aderivs	a logical for whether to use analytic derivatives (instead of numerical)
unbiasedv	a logical for whether to use the unbiased variance instead of maxlik (for the normal)
pwm	a logical for whether to use PWM instead of maxlik (for the GEV)
minxi	minimum value for EVT shape parameter
maxxi	maximum value for EVT shape parameter

Value

Two vectors

fitdistcp documentation built on June 8, 2025, 1:04 p.m.