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#'@title Probability density function
#'
#'@description This function computes the probability density function of a univariate distribution with unconstrained parameters
#'
#'@param family distribution name; run the command distributions() for help
#'@param y observations
#'@param param parameters of the distribution (unconstrained, in R)
#'@param size additional parameter for some discrete distributions
#'
#'@return \item{f}{pdf}
#'
#'@export
#'@keywords internal
PDF_unc<-function(family,y,param,size=0){
switch(family,
"asymexppower" = { ## [R+, R+, 01]
f = VaRES::daep(y, q1 = exp(param[1]), q2 = exp(param[2]), alpha = 1/(1+exp(-param[3])))
} ,
"asymlaplace" = { ## [R, R+, R+]
f = VGAM::dalap(y, location = param[1], scale = exp(param[2]), kappa = exp(param[3]))
} ,
"asympower" = { ## [01, R+, R+]
f = VaRES::dasypower(y, a = 1/(1+exp(-param[1])), lambda = exp(param[2]), delta = exp(param[3]))
} ,
"asymt" = { ## [R+, R+, 01, R]
f = VaRES::dast(y-param[4], nu1 = exp(param[1]), nu2 = exp(param[2]), alpha = 1/(1+exp(-param[3])) )
} ,
"beard" = { ## [R+, R+, R+]
f = VaRES::dbeard(y, a = exp(param[1]), b = exp(param[2]), rho = exp(param[3]))
} ,
"benini" = { ## [R, R+]
f = VGAM::dbenini(y, y0 = param[1], shape = exp(param[2]))
} ,
"benford" = { ## [1 ou 2]
if (exp(param[1])>2) {
f = VGAM::dbenf(y, ndigits = 2)
} else if (exp(param[1])<1) {
f = VGAM::dbenf(y, ndigits = 1)
} else {
f = VGAM::dbenf(y, ndigits = round(param[1]))
}
} ,
"bernoulli" = { ## [01]
f = extraDistr::dbern(y, prob = 1/(1+exp(-param[1])) )
} ,
"beta" = { ## [R+, R+]
f = stats::dbeta(y, shape1 = exp(param[1]), shape2 = exp(param[2]))
} ,
"betabinomial" = { ## [N+, R+, R+]
f = extraDistr::dbbinom(y, size = size, alpha = exp(param[1]), beta = exp(param[2]))
} ,
"betageometric" = { ## [R+, R+]
f = VGAM::dbetageom(y, shape1 = exp(param[1]), shape2 = exp(param[2]))
} ,
"betanegativebinomial" = { ## [N+, R+, R+]
f = extraDistr::dbnbinom(y, size = size, alpha = exp(param[1]), beta = exp(param[2]))
} ,
"betaburr" = { ## [R+, R+, R+, R+]
f = VaRES::dbetaburr(y, a = exp(param[1]), b = exp(param[2]), c = exp(param[3]), d = exp(param[4]))
} ,
"betaburr7" = { ## [R+, R+]
f = VaRES::dbetaburr7(y, a = exp(param[1]), b = exp(param[2]), c = exp(param[3]), k = exp(param[4]))
} ,
"betaexponential" = { ## [R+, R+, R+]
f = VaRES::dbetaexp(y, lambda = exp(param[1]), a = exp(param[2]), b = exp(param[3]))
} ,
"betafrechet" = { ## [R+, R+]
f = VaRES::dbetafrechet(y, a = exp(param[1]), b = exp(param[2]), alpha = exp(param[3]),
sigma = exp(param[4]))
} ,
"betagompertz" = { ## [R+, R+]
f = VaRES::dbetagompertz(y, b = exp(param[1]), c = exp(param[2]), d = exp(param[3]),
eta = exp(param[4]))
} ,
"betagumbel" = { ## [R+, R+]
f = VaRES::dbetagumbel(y, a = exp(param[1]), b = exp(param[2]), mu = param[3],
sigma = exp(param[4]))
} ,
"betagumbel2" = { ## [R+, R+]
f = VaRES::dbetagumbel2(y, a = exp(param[1]), b = exp(param[2]), c = exp(param[3]), d = exp(param[4]))
} ,
"betalognormal" = { ## [R+, R+]
f = VaRES::dbetalognorm(y, a = exp(param[1]), b = exp(param[2]), mu = param[3], sigma = exp(param[4]))
} ,
"betalomax" = { ## [R+, R+, R+, R+]
f = VaRES::dbetalomax(y, a = exp(param[1]), b = exp(param[2]), alpha = exp(param[3]),
lambda = exp(param[4]))
} ,
"betanormal" = { ## [R+, R+, R, R+]
f = VGAM::dbetanorm(y, shape1 = exp(param[1]), shape2 = exp(param[2]),
mean = param[3], sd = exp(param[4]))
} ,
"betaprime" = { ## [R+, R+, R+]
f = extraDistr::dbetapr(y, shape1 = exp(param[1]), shape2 = exp(param[2]), scale = exp(param[3]))
} ,
"betaweibull" = { ## [R+, R+, R+, R+]
f = VaRES::dbetaweibull(y, a = exp(param[1]), b = exp(param[2]), alpha = exp(param[3]),
sigma = exp(param[4]))
} ,
"bhattacharjee" = { ## [R, R+, R+]
f = extraDistr::dbhatt(y, mu = param[1], sigma = exp(param[2]), a = exp(param[3]))
} ,
"binomial" = { ## [N+, 01]
f = stats::dbinom(y, size = size, prob = 1/(1+exp(-param[1])) )
} ,
"birnbaumsaunders" = { ## [R+, R+, R]
f = extraDistr::dfatigue(y, alpha = exp(param[1]), beta = exp(param[2]), mu = param[3])
} ,
"boxcox" = { ## [R+, R+, R+]
f = rmutil::dboxcox(y, m = exp(param[1]), s = exp(param[2]), f = exp(param[3]))
} ,
"burr" = { ## [R+, R+, R+]
f = actuar::dburr(y, shape1 = exp(param[1]), shape2 = exp(param[2]), scale = exp(param[3]))
} ,
"burr2param" = { ## [R+, R+]
f = VaRES::dburr(y, a = exp(param[1]), b = exp(param[2]))
} ,
"cauchy" = { ## [R, R+]
f = stats::dcauchy(y, location = param[1], scale = exp(param[2]))
} ,
"chen" = { ## [R+, R+]
f = VaRES::dchen(y, b = exp(param[1]), lambda = exp(param[2]))
} ,
"chi" = { ## [R+]
f = EnvStats::dchi(y, df = exp(param[1]))
} ,
"chisquared" = { ## [R+]
f = stats::dchisq(y, df = exp(param[1]))
} ,
"clg" = { ## [R+, R+, R]
f = VaRES::dclg(y, a = exp(param[1]), b = exp(param[2]), param[3])
} ,
"complementarybeta" = { ## [R+, R+]
f = VaRES::dcompbeta(y, a = exp(param[1]), b = exp(param[2]))
} ,
"dagum" = { ## [R+, R+, R+]
f = VGAM::ddagum(y, scale = exp(param[1]), shape1.a = exp(param[2]), shape2.p = exp(param[3]))
} ,
"diffzeta" = { ## [R+, >1]
f = VGAM::ddiffzeta(y, shape = exp(param[1]), start = 1+exp(-param[2]) )
} ,
"discretegamma" = { ## [R+, R+]
f = extraDistr::ddgamma(y, shape = exp(param[1]), scale = exp(param[2]))
} ,
"discretelaplace" = { ## [R, 01]
f = extraDistr::ddlaplace(y, location = param[1], scale = 1/(1+exp(-param[2])) )
} ,
"discretenormal" = { ## [R, R+]
f = extraDistr::ddnorm(y, mean = param[1], sd = exp(param[2]))
} ,
"discreteweibull" = { ## [01, R+]
f = extraDistr::ddweibull(y, shape1 = 1/(1+exp(-param[1])), shape2 = exp(param[2]))
} ,
"doubleweibull" = { ## [R+, R, R+]
f = VaRES::ddweibull(y, c = exp(param[1]), mu = param[2], sigma = exp(param[3]))
} ,
"ev" = {
## [R, R+]
f = VGAM::dgev(y, location = param[1], scale = exp(param[2]), shape = 0)
} ,
"exponential" = { ## [R+]
f = stats::dexp(y, rate = exp(param[1]))
} ,
"exponentialextension" = { ## [R+, R+]
f = VaRES::dexpext(y, lambda = exp(param[1]), a = exp(param[2]))
} ,
"exponentialgeometric" = { ## [R+, 01]
f = VGAM::dexpgeom(y, scale = exp(param[1]), shape = 1/(1+exp(-param[2])) )
} ,
"exponentiallogarithmic" = { ## [R+, 01]
f = VGAM::dexplog(y, scale = exp(param[1]), shape = 1/(1+exp(-param[2])) )
} ,
"exponentialpoisson" = { ## [R+, R+]
f = VaRES::dexppois(y, b = exp(param[1]), lambda = exp(param[2]))
} ,
"exponentialpower" = { ## [R, R+, R+]
f = VaRES::dexppower(y, mu = param[1], sigma = exp(param[2]), a = exp(param[3]))
} ,
"exponentiatedexponential" = { ## [R+, R+]
f = VaRES::dexpexp(y, lambda = exp(param[1]), a = exp(param[2]))
} ,
"exponentiatedlogistic" = { ## [R+, R+]
f = VaRES::dexplogis(y, a = exp(param[1]), b = exp(param[2]))
} ,
"exponentiatedweibull" = { ## [R+, R+, R+]
f = VaRES::dexpweibull(y, a = exp(param[1]), alpha = exp(param[2]), sigma = exp(param[3]))
} ,
"F" = { ## [R+, R+]
f = stats::df(y, df1 = exp(param[1]), df2 = exp(param[2]))
} ,
"fellerpareto" = { ## [R(mini), R+, R+, R+, R+]
f = actuar::dfpareto(y, min = param[1], shape1 = exp(param[2]),
shape2 = exp(param[3]), shape3 = exp(param[4]),
scale = exp(param[5]))
} ,
"fisk" = { ## [R+, R+]
f = VGAM::dfisk(y, scale = exp(param[1]), shape1.a = exp(param[2]))
} ,
"foldednormal" = { ## [R, R+]
f = VGAM::dfoldnorm(y, mean = param[1], sd = exp(param[2]))
} ,
"frechet" = { ## [R+, R, R+]
f = VGAM::dfrechet(y, shape = exp(param[1]), location = param[2], scale = exp(param[3]))
} ,
"gamma" = { ## [R+, R+]
f = stats::dgamma(y, shape = exp(param[1]), scale = exp(param[2]))
} ,
"gaussian" = { ## [R, R+]
f = stats::dnorm(y, mean = param[1], sd = exp(param[2]))
} ,
"gev" = { ## [R, R+, R]
f = VGAM::dgev(y, location = param[1], scale = exp(param[2]), shape = param[3])
} ,
"geninvbeta" = { ## [R+, R+, R+]
f = VaRES::dgeninvbeta(y, a = exp(param[1]), c = exp(param[2]), d = exp(param[3]))
} ,
"genlogis" = { ## [R+, R, R+]
f = VaRES::dgenlogis(y, a = exp(param[1]), mu = param[2], sigma = exp(param[3]))
} ,
"genlogis3" = { ## [R+, R, R+]
f = VaRES::dgenlogis3(y, a = exp(param[1]), mu = param[2], sigma = exp(param[3]))
} ,
"genlogis4" = { ## [R+, R+, R, R+]
f = VaRES::dgenlogis4(y, a = exp(param[1]), alpha = exp(param[2]), mu = param[3], sigma = exp(param[4]))
} ,
"genpowerweibull" = { ## [R+, R+]
f = VaRES::dgenpowerweibull(y, a = exp(param[1]), theta = exp(param[2]))
} ,
"geometric" = { ## [01]
f = stats::dgeom(y, prob = 1/(1+exp(-param[1])) )
} ,
"generalizedhyperbolic" = { ## [R, R+, R+, R, R] [mu, delta, alpha, beta, lambda] (avec alpha^2 > beta^2)
f = GeneralizedHyperbolic::dghyp(y, mu = param[1], delta = exp(param[2]),
alpha = exp(param[3]),
beta = exp(param[3]-10e-15) * ( exp(2*param[4])-1 ) / ( exp(2*param[4])+1 ),
lambda = param[5])
} ,
"generalizedlambda" = { ## [R, R+, R, R]
f = GLDEX::dgl(y, lambda1 = param[1], lambda2 = exp(param[2]), lambda3 = param[3], lambda4 = param[4])
} ,
"generalizedt" = { ## [R, R+, R+, R+]
f = gamlss.dist::dGT(y, mu = param[1], sigma = exp(param[2]), nu = exp(param[3]), tau = exp(param[4]))
} ,
"gompertz" = { ## [R+, R+]
f = ssdtools::dgompertz(y, lscale = exp(param[1]), lshape = exp(param[2]))
} ,
"gpd" = { ## [R, R+, R]
f = VGAM::dgpd(y, location = param[1], scale = exp(param[2]), shape = param[3])
} ,
"gumbel" = { ## [R, R+]
f = VGAM::dgumbel(y, location = param[1], scale = exp(param[2]))
} ,
"gumbel2" = { ## [R+, R+]
f = VGAM::dgumbelII(y, scale = exp(param[1]), shape = exp(param[2]))
} ,
"halfcauchy" = { ## [R+]
f = extraDistr::dhcauchy(y, sigma = exp(param[1]))
} ,
"halflogistic" = { ## [R+]
f = VaRES::dhalflogis(y, lambda = exp(param[1]))
} ,
"halfnormal" = { ## [R+]
f = extraDistr::dhnorm(y, sigma = exp(param[1]))
} ,
"halft" = { ## [R+, R+]
f = extraDistr::dht(y, nu = exp(param[1]), sigma = exp(param[2]))
} ,
"hjorth" = { ## [R+, R+, R+]
f = rmutil::dhjorth(y, m = exp(param[1]), s = exp(param[2]), f = exp(param[3]))
} ,
"hblaplace" = { ## [01, R, R+]
f = VaRES::dHBlaplace(y, a = 1/(1+exp(-param[1])), theta = param[2], phi = exp(param[3]))
} ,
"hyperbolic" = { ## [R, R+, R+, R]
f = GeneralizedHyperbolic::dhyperb(y, mu = param[1], delta = exp(param[2]),
alpha = exp(param[3]),
beta = exp(param[3]) * ( exp(2*param[4])-1 ) / ( exp(2*param[4])+1 ))
} ,
"huber" = { ## [R, R+]
f = extraDistr::dhuber(y, mu = param[1], sigma = exp(param[2]))
} ,
"hzeta" = { ## [R+]
f = VGAM::dhzeta(y, shape = exp(param[1]))
} ,
"inversebeta" = { ## [R+, R+]
f = VaRES::dinvbeta(y, a = exp(param[1]), b = exp(param[2]))
} ,
"inverseburr" = { ## [R+, R+, R+]
f = actuar::dinvburr(y, shape1 = exp(param[1]), shape2 = exp(param[2]), scale = exp(param[3]))
} ,
"inversechisquared" = { ## [R+]
f = extraDistr::dinvchisq(y, nu = exp(param[1]))
} ,
"inverseexponential" = { ## [R+]
f = actuar::dinvexp(y, scale = exp(param[1]))
} ,
"inverseexpexponential" = { ## [R+, R+]
f = VaRES::dinvexpexp(y, lambda = exp(param[1]), a = exp(param[2]))
} ,
"inversegamma" = { ## [R+, R+]
f = extraDistr::dinvgamma(y, alpha = exp(param[1]), beta = exp(param[2]))
} ,
"inverselomax" = { ## [R+, R+]
f = VGAM::dinv.lomax(y, scale = exp(param[1]), shape2.p = exp(param[2]))
} ,
"inverseparalogistic" = { ## [R+, R+]
f = actuar::dinvparalogis(y, shape = exp(param[1]), scale = exp(param[2]))
} ,
"inversepareto" = { ## [R+, R+]
f = actuar::dinvpareto(y, shape = exp(param[1]), scale = exp(param[2]))
} ,
"inversetransformedgamma" = { ## [R+, R+, R+]
f = actuar::dinvtrgamma(y, shape1 = exp(param[1]), shape2 = exp(param[2]), scale = exp(param[3]))
} ,
"inverseweibull" = { ## [R+, R+]
f = actuar::dinvweibull(y, shape = exp(param[1]), scale = exp(param[2]))
} ,
"kumaraswamy" = { ## [R+, R+]
f = VGAM::dkumar(y, shape1 = exp(param[1]), shape2 = exp(param[2]))
} ,
"kumaraswamyexponential" = { ## [R+, R+, R+]
f = VaRES::dkumexp(y, lambda = exp(param[1]), a = exp(param[2]), b = exp(param[3]))
} ,
"kumaraswamygamma" = { ## [R+, R+, R+, R+]
f = VaRES::dkumgamma(y, a = exp(param[1]), b = exp(param[2]), c = exp(param[3]), d = exp(param[4]))
} ,
"kumaraswamygumbel" = { ## [R+, R+, R, R+]
f = VaRES::dkumgumbel(y, a = exp(param[1]), b = exp(param[2]), mu = param[3],
sigma = exp(param[4]))
} ,
"kumaraswamyhalfnormal" = { ## [R+, R+, R+]
f = VaRES::dkumhalfnorm(y, sigma = exp(param[1]), a = exp(param[2]), b = exp(param[3]))
} ,
"kumaraswamyloglogistic" = { ## [R+, R+, R+, R+]
f = VaRES::dkumloglogis(y, a = exp(param[1]), b = exp(param[2]), alpha = exp(param[3]),
beta = exp(param[4]))
} ,
"kumaraswamynormal" = { ## [R, R+, R+, R+]
f = VaRES::dkumnormal(y, mu = param[1], sigma = exp(param[2]), a = exp(param[3]),
b = exp(param[4]))
} ,
"kumaraswamyweibull" = { ## [R+, R+, R+, R+]
f = VaRES::dkumweibull(y, a = exp(param[1]), b = exp(param[2]), alpha = exp(param[3]),
sigma = exp(param[4]))
} ,
"laplace" = { ## [R, R+]
f = extraDistr::dlaplace(y, mu = param[1], sigma = exp(param[2]))
} ,
"levy" = { ## [R, R+]
f = rmutil::dlevy(y, m = param[1], s = exp(param[2]))
} ,
"linearfailurerate" = { ## [R+, R+]
f = VaRES::dlfr(y, a = exp(param[1]), b = exp(param[2]))
} ,
"lindley" = { ## [R+]
f = VGAM::dlind(y, theta = exp(param[1]))
} ,
"libbynovickbeta" = { ## [R+, R+, R+]
f = VaRES::dLNbeta(y, lambda = exp(param[1]), a = exp(param[2]), b = exp(param[3]))
} ,
"logcauchy" = { ## [R, R+]
f = VaRES::dlogcauchy(y, mu = param[1], sigma = exp(param[2]))
} ,
"loggamma" = { ## [R, R+, R+]
f = VGAM::dlgamma(y, location = param[1], scale = exp(param[2]), shape = exp(param[3]))
} ,
"loggumbel" = { ## [R, R+]
f = ssdtools::dlgumbel(y, llocation = param[1], lscale = exp(param[2]))
} ,
"loglaplace" = { ## [R, R+, R+]
f = VGAM::dloglap(y, location.ald = param[1], scale.ald = exp(param[2]), kappa = exp(param[3]))
} ,
"loglog" = { ## [R+, >1]
f = VaRES::dloglog(y, a = exp(param[1]), lambda = 1 + exp(-param[2]) )
} ,
"loglogistic" = { ## [R+, R+]
f = actuar::dllogis(y, shape = exp(param[1]), scale = exp(param[2]))
} ,
"lognormal" = { ## [R, R+]
f = stats::dlnorm(y, meanlog = param[1], sdlog = exp(param[2]))
} ,
"lognormal3" = { ## [R, R+, R]
f = EnvStats::dlnorm3(y, meanlog = param[1], sdlog = exp(param[2]), threshold = param[3])
} ,
"logistic" = { ## [R, R+]
f = stats::dlogis(y, location = param[1], scale = exp(param[2]))
} ,
"logisticexponential" = { ## [R+, R+]
f = VaRES::dlogisexp(y, lambda = exp(param[1]), a = exp(param[2]))
} ,
"logisticrayleigh" = { ## [R+, R+]
f = VaRES::dlogisrayleigh(y, a = exp(param[1]), lambda = exp(param[2]))
} ,
"logseries" = { ## [01]
f = extraDistr::dlgser(y, theta = 1/(1+exp(-param[1])) )
} ,
"lomax" = { ## [R+, R+]
f = VGAM::dlomax(y, scale = exp(param[1]), shape3.q = exp(param[2]))
} ,
"makeham" = { ## [R+, R+, R+]
f = VGAM::dmakeham(y, scale = exp(param[1]), shape = exp(param[2]), epsilon = exp(param[3]))
} ,
"maxwell" = { ## [R+]
f = VGAM::dmaxwell(y, rate = exp(param[1]))
} ,
"mcgilllaplace" = { ## [R, R+, R+]
f = VaRES::dMlaplace(y, theta = param[1], phi = exp(param[2]), psi = exp(param[3]))
} ,
"moexponential" = { ## [R+, R+]
f = VaRES::dmoexp(y, lambda = exp(param[1]), a = exp(param[2]))
} ,
"moweibull" = { ## [R+, R+, R+]
f = VaRES::dmoweibull(y, a = exp(param[1]), b = exp(param[2]), lambda = exp(param[3]))
} ,
"nakagami" = { ## [R+, R+]
f = VGAM::dnaka(y, scale = exp(param[1]), shape = exp(param[2]))
} ,
"ncchisquared" = { ## [R+, R+]
f = stats::dchisq(y, df = exp(param[1]), ncp = exp(param[2]))
} ,
"ncF" = { ## [R+, R+, R+]
f = stats::df(y, df1 = exp(param[1]), df2 = exp(param[2]), ncp = exp(param[3]))
} ,
"negativebinomial" = { ## [N+, 01]
f = stats::dnbinom(y, size = size, prob = 1/(1+exp(-param[1])) )
} ,
"normalinversegaussian" = { ## [R, R+, R+, R]
f = GeneralizedHyperbolic::dnig(y, mu = param[1], delta = exp(param[2]),
alpha = exp(param[3]),
beta = exp(param[3]) * ( exp(2*param[4])-1 ) / ( exp(2*param[4])+1 ))
} ,
"nsbeta" = { ## [R+, R+, R(min), R(maxi)]
f = extraDistr::dnsbeta(y, shape1 = exp(param[1]), shape2 = exp(param[2]),
min = param[3], max = param[4])
} ,
"paralogistic" = { ## [R+, R+]
f = VGAM::dparalogistic(y, scale = exp(param[1]), shape1.a = exp(param[2]))
} ,
"pareto" = { ## [R+]
f = extraDistr::dpareto(y, a = exp(param[1]), b = min(y))
} ,
"paretopositivestable" = { ## [R+, R+, R+]
f = VaRES::dparetostable(y, lambda = exp(param[1]), nu = exp(param[2]), sigma = exp(param[3]))
} ,
"pareto1" = { ## [R+, R+]
f = VGAM::dparetoI(y, scale = exp(param[1]), shape = exp(param[2]))
} ,
"pareto2" = { ## [R, R+, R+]
f = VGAM::dparetoII(y, location = param[1], scale = exp(param[2]), shape = exp(param[3]))
} ,
"pareto3" = { ## [R, R+, R+]
f = VGAM::dparetoIII(y, location = param[1], scale = exp(param[2]), inequality = exp(param[3]))
} ,
"pareto4" = { ## [R, R+, R+, R+]
f = VGAM::dparetoIV(y, location = param[1], scale = exp(param[2]), inequality = exp(param[3]),
shape = exp(param[4]))
} ,
"perks" = { ## [R+, R+]
f = VGAM::dperks(y, scale = exp(param[1]), shape = exp(param[2]))
} ,
"pctalaplace" = { ## [R+, R]
f = VaRES::dPCTAlaplace(y, a = exp(param[1]), theta = param[2])
} ,
"poisson" = { ## [R+]
f = stats::dpois(y, lambda = exp(param[1]))
} ,
"power1" = { ## [R+]
f = VaRES::dpower1(y, a = exp(param[1]))
} ,
"power2" = { ## [R+]
f = VaRES::dpower2(y, b = exp(param[1]))
} ,
"powerdistribution" = { ## [R+, R+]
f = extraDistr::dpower(y, alpha = exp(param[1]), beta = exp(param[1]))
} ,
"powerexponential" = { ## [R, R+, R+]
f = rmutil::dpowexp(y, m = param[1], s = exp(param[2]), f = exp(param[3]))
} ,
"rayleigh" = { ## [R+]
f = VGAM::drayleigh(y, scale = exp(param[1]))
} ,
"reflectedgamma" = { ## [R+, R, R+]
f = VaRES::drgamma(y, a = exp(param[1]), theta = param[2], phi = exp(param[3]))
} ,
"rice" = { ## [R+, R+]
f = VGAM::drice(y, sigma = exp(param[1]), vee = exp(param[2]))
} ,
"scaledchisquared" = { ## [R+, R+]
f = extraDistr::dinvchisq(y, nu = exp(param[1]), tau = exp(param[2]))
} ,
"schabe" = { ## [R+, R+]
f = VaRES::dschabe(y, gamma = exp(param[1]), theta = exp(param[2]))
} ,
"simplex" = { ## [01, R+]
f = rmutil::dsimplex(y, m = 1/(1+exp(-param[1])), s = exp(param[2]))
} ,
"skewedlaplace" = { ## [R, R+, R+]
f = rmutil::dskewlaplace(y, m = param[1], s = exp(param[2]), f = exp(param[3]))
} ,
"skewedt" = { ## [R+, R+]
f = skewt::dskt(y, df = exp(param[1]), gamma = exp(param[2]))
} ,
"skewedtfourparam" = { ## [R, R+, R, R+ (<25)]
f = sn::dst(y, xi = param[1], omega = exp(param[2]), alpha = param[3], nu = 25/(1+exp(-param[4])) )
} ,
"skewednormal" = { ## [R, R+, R]
f = sn::dsn(y, xi = param[1], omega = exp(param[2]), alpha = param[3])
} ,
"skewedgeneralizedt" = { ## [R, R+, -1+1, R+(>1), R+(>1)]
f = sgt::dsgt(y, mu = param[1], sigma = exp(param[2]),
lambda = (exp(2*param[3])-1)/(exp(2*param[3])+1),
p = 1+exp(-param[4]))
} ,
"skewedexponentialpower" = { ## [R, R+, R, R+]
f = gamlss.dist::dSEP(y, mu = param[1], sigma = exp(param[2]), nu = param[3], tau = exp(param[4]))
} ,
"slash" = { ## [R, R+]
f = extraDistr::dslash(y, mu = param[1], sigma = exp(param[2]))
} ,
"stacy" = { ## [R+, R+, R+]
f = VaRES::dstacygamma(y, gamma = exp(param[1]), c = exp(param[2]), theta = exp(param[3]))
} ,
"t" = { ## [R, R+, R+(<25)]
f = stats::dt((y-param[1])/exp(param[2]), df = 25/(1+exp(-param[3])) ) / exp(param[2])
} ,
"tobit" = { ## [R, R+]
f = VGAM::dtobit(y, mean = param[1], sd = exp(param[2]))
} ,
"topple" = { ## [01]
f = VGAM::dtopple(y, shape = 1/(1+exp(-param[1])))
} ,
"transformedbeta" = { ## [R+, R+, R+, R+]
f = actuar::dtrbeta(y, shape1 = exp(param[1]), shape2 = exp(param[2]), shape3 = exp(param[3]),
scale = exp(param[4]))
} ,
"transformedgamma" = { ## [R+, R+, R+]
f = actuar::dtrgamma(y, shape1 = exp(param[1]), shape2 = exp(param[2]), scale = exp(param[3]))
} ,
"truncatednormal" = { ## [R, R+, R(min), R(max)]
f = extraDistr::dtnorm(y, mean = param[1], sd = exp(param[2]), a = param[3],
b = param[4])
} ,
"truncatedpareto" = { ## [R+(mini), R+(maxi), R+]
f = VGAM::dtruncpareto(y, lower = exp(param[2]), upper = exp(param[2]), shape = exp(param[3]))
} ,
"twosidedpower" = { ## [01, R+]
f = rmutil::dtwosidedpower(y, m = 1/(1+exp(-param[1])), s = exp(param[2]))
} ,
"wald" = { ## [R, R+]
f = extraDistr::dwald(y, mu = param[1], lambda = exp(param[2]))
} ,
"weibull" = { ## [R+, R+]
f = stats::dweibull(y, shape = exp(param[1]), scale = exp(param[2]))
} ,
"xie" = { ## [R+, R+, R+]
f = VaRES::dxie(y, a = exp(param[1]), b = exp(param[2]), lambda = exp(param[3]))
} ,
"yules" = { ## [R+] mais > 0.5
f = VGAM::dyules(y, shape = 0.5+exp(-param[1]))
} ,
)
f[is.nan(f)] <- 0
return(f)
}
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