Nothing
.start.smith <- function(data, coord, covariables, loc.form, scale.form, shape.form,
print.start.values = TRUE, method = "Nelder",
iso = TRUE, ...){
n.site <- ncol(data)
if (iso && (method == "Nelder"))
method2 <- "BFGS"
else if (method %in% c("nlm", "nlminb"))
method2 <- "Nelder"
else
method2 <- method
if (ncol(coord) == 2)
param <- c("cov11", "cov12", "cov22")
else
param <- c("cov11", "cov12", "cov13", "cov22", "cov23", "cov33")
fixed.param <- list(...)[names(list(...)) %in% param]
idx.cov <- which(names(fixed.param) %in% param)
fixed.param.cov <- fixed.param[idx.cov]
fixed.param.gev <- fixed.param[-idx.cov]
if (print.start.values)
cat("Computing appropriate starting values\n")
if (length(fixed.param.cov) > 0){
args <- c(list(data = data, coord = coord, marge = "emp", iso = iso, method = method2),
fixed.param.cov)
covs <- do.call("fitcovmat", args)$fitted
}
else
covs <- fitcovmat(data, coord, marge = "emp", iso = iso, method = method2)$fitted
if (iso){
covs <- covs[1]
names(covs) <- "cov"
}
args <- c(list(data = data, covariables = as.matrix(covariables), loc.form = loc.form,
scale.form = scale.form, shape.form = shape.form, method = method, warn = FALSE), fixed.param.gev)
spatgev <- do.call("fitspatgev", args)
frech <- data
gev <- predict(spatgev)
for (i in 1:n.site)
frech[,i] <- gev2frech(frech[,i], gev[i,"loc"], gev[i,"scale"], gev[i,"shape"])
args <- c(list(data = frech, coord = coord, fit.marge = FALSE, start = as.list(covs),
iso = iso, warn = FALSE, method = method),
fixed.param.cov)
covs <- do.call("smithfull", args)
start <- c(as.list(covs$fitted), as.list(spatgev$param))
if (print.start.values){
cat("Starting values are defined\n")
cat("Starting values are:\n")
print(c(covs$fitted, spatgev$fitted))
cat("\n \n \n")
}
return(start)
}
.start.schlather <- function(data, coord, covariables, cov.mod, loc.form,
scale.form, shape.form, print.start.values = TRUE,
method = "Nelder", ...){
n.site <- ncol(data)
param <- c("nugget", "range", "smooth", "smooth2")
fixed.param <- list(...)[names(list(...)) %in% param]
idx.cov <- which(names(fixed.param) %in% param)
fixed.param.cov <- fixed.param[idx.cov]
fixed.param.gev <- fixed.param[-idx.cov]
if (print.start.values)
cat("Computing appropriate starting values\n")
if (length(fixed.param.cov) > 0){
args <- c(list(data = data, coord = coord, cov.mod = cov.mod,
marge = "emp"), fixed.param.cov)
cov.param <- do.call("fitcovariance", args)$fitted
}
else
cov.param <- fitcovariance(data, coord, cov.mod, marge = "emp")$fitted
args <- c(list(data = data, covariables = as.matrix(covariables), loc.form = loc.form,
scale.form = scale.form, shape.form = shape.form,
method = method, warn = FALSE), fixed.param.gev)
spatgev <- do.call("fitspatgev", args)
frech <- data
gev <- predict(spatgev)
for (i in 1:n.site)
frech[,i] <- gev2frech(frech[,i], gev[i,"loc"], gev[i,"scale"], gev[i,"shape"])
args <- c(list(data = frech, coord = coord, cov.mod = cov.mod, fit.marge = FALSE,
start = as.list(cov.param), warn = FALSE, method = method), fixed.param.cov)
cov.param <- do.call("schlatherfull", args)
start <- c(as.list(cov.param$param), as.list(spatgev$param))
if (print.start.values){
cat("Starting values are defined\n")
cat("Starting values are:\n")
print(c(cov.param$fitted, spatgev$fitted))
}
return(start)
}
.start.schlatherind <- function(data, coord, covariables, cov.mod, loc.form,
scale.form, shape.form, print.start.values = TRUE,
method = "Nelder", ...){
n.site <- ncol(data)
param <- c("alpha", "nugget", "range", "smooth", "smooth2")
fixed.param <- list(...)[names(list(...)) %in% param]
idx.cov <- which(names(fixed.param) %in% param)
fixed.param.cov <- fixed.param[idx.cov]
fixed.param.gev <- fixed.param[-idx.cov]
if (print.start.values)
cat("Computing appropriate starting values\n")
if (length(fixed.param.cov) > 0){
args <- c(list(data = data, coord = coord, cov.mod = paste("i", cov.mod, sep=""),
marge = "emp"), fixed.param.cov)
cov.param <- do.call("fitcovariance", args)$fitted
}
else
cov.param <- fitcovariance(data, coord, paste("i", cov.mod, sep=""),
marge = "emp")$fitted
args <- c(list(data = data, covariables = as.matrix(covariables), loc.form = loc.form,
scale.form = scale.form, shape.form = shape.form,
method = method, warn = FALSE), fixed.param.gev)
spatgev <- do.call("fitspatgev", args)
frech <- data
gev <- predict(spatgev)
for (i in 1:n.site)
frech[,i] <- gev2frech(frech[,i], gev[i,"loc"], gev[i,"scale"], gev[i,"shape"])
args <- c(list(data = frech, coord = coord, cov.mod = cov.mod, fit.marge = FALSE,
start = as.list(cov.param), warn = FALSE, method = method), fixed.param.cov)
cov.param <- do.call("schlatherindfull", args)
start <- c(as.list(cov.param$param), as.list(spatgev$param))
if (print.start.values){
cat("Starting values are defined\n")
cat("Starting values are:\n")
print(c(cov.param$fitted, spatgev$fitted))
}
return(start)
}
.start.geomgauss <- function(data, coord, covariables, cov.mod, loc.form,
scale.form, shape.form, print.start.values = TRUE,
method = "Nelder", ...){
n.site <- ncol(data)
param <- c("sigma2", "nugget", "range", "smooth", "smooth2")
fixed.param <- list(...)[names(list(...)) %in% param]
idx.cov <- which(names(fixed.param) %in% param)
fixed.param.cov <- fixed.param[idx.cov]
fixed.param.gev <- fixed.param[-idx.cov]
if (print.start.values)
cat("Computing appropriate starting values\n")
if (length(fixed.param.cov) > 0){
args <- c(list(data = data, coord = coord, cov.mod = paste("g", cov.mod, sep=""),
marge = "emp"), fixed.param.cov)
cov.param <- do.call("fitcovariance", args)$fitted
}
else
cov.param <- fitcovariance(data, coord, paste("g", cov.mod, sep=""),
marge = "emp")$fitted
args <- c(list(data = data, covariables = as.matrix(covariables), loc.form = loc.form,
scale.form = scale.form, shape.form = shape.form,
method = method, warn = FALSE), fixed.param.gev)
spatgev <- do.call("fitspatgev", args)
frech <- data
gev <- predict(spatgev)
for (i in 1:n.site)
frech[,i] <- gev2frech(frech[,i], gev[i,"loc"], gev[i,"scale"], gev[i,"shape"])
args <- c(list(data = frech, coord = coord, cov.mod = cov.mod, fit.marge = FALSE,
start = as.list(cov.param), warn = FALSE, method = method), fixed.param.cov)
cov.param <- do.call("geomgaussfull", args)
start <- c(as.list(cov.param$param), as.list(spatgev$param))
if (print.start.values){
cat("Starting values are defined\n")
cat("Starting values are:\n")
print(c(cov.param$fitted, spatgev$fitted))
}
return(start)
}
.start.extremalt <- function(data, coord, covariables, cov.mod, loc.form,
scale.form, shape.form, print.start.values = TRUE,
method = "Nelder", ...){
n.site <- ncol(data)
param <- c("nugget", "range", "smooth", "smooth2", "DoF")
fixed.param <- list(...)[names(list(...)) %in% param]
idx.cov <- which(names(fixed.param) %in% param)
fixed.param.cov <- fixed.param[idx.cov]
fixed.param.gev <- fixed.param[-idx.cov]
if (print.start.values)
cat("Computing appropriate starting values\n")
if (length(fixed.param.cov) > 0){
args <- c(list(data = data, coord = coord, cov.mod = paste("t", cov.mod, sep=""),
marge = "emp"), fixed.param.cov)
cov.param <- do.call("fitcovariance", args)$fitted
}
else
cov.param <- fitcovariance(data, coord, paste("t", cov.mod, sep=""),
marge = "emp")$fitted
args <- c(list(data = data, covariables = as.matrix(covariables), loc.form = loc.form,
scale.form = scale.form, shape.form = shape.form,
method = method, warn = FALSE), fixed.param.gev)
spatgev <- do.call("fitspatgev", args)
frech <- data
gev <- predict(spatgev)
for (i in 1:n.site)
frech[,i] <- gev2frech(frech[,i], gev[i,"loc"], gev[i,"scale"], gev[i,"shape"])
args <- c(list(data = frech, coord = coord, cov.mod = cov.mod, fit.marge = FALSE,
start = as.list(cov.param), warn = FALSE, method = method), fixed.param.cov)
cov.param <- do.call("extremaltfull", args)
start <- c(as.list(cov.param$param), as.list(spatgev$param))
if (print.start.values){
cat("Starting values are defined\n")
cat("Starting values are:\n")
print(c(cov.param$fitted, spatgev$fitted))
}
return(start)
}
.start.nsgeomgauss <- function(data, coord, covariables, cov.mod, loc.form,
scale.form, shape.form, sigma2.form,
print.start.values = TRUE, method = "Nelder",
...){
n.site <- ncol(data)
sigma2.terms <- terms(sigma2.form)
if (length(attributes(sigma2.terms)$factor) == 0)
n.sigma2coeff <- attributes(sigma2.terms)$intercept
else
n.sigma2coeff <- attributes(sigma2.terms)$intercept +
ncol(attributes(sigma2.terms)$factors)
if (n.sigma2coeff == 1)
sigma2.names <- "sigma2"
else
sigma2.names <- paste("sigma2Coeff", 1:n.sigma2coeff, sep="")
param <- c(sigma2.names, "nugget", "range", "smooth", "smooth2")
fixed.param <- list(...)[names(list(...)) %in% param]
idx.cov <- which(names(fixed.param) %in% param)
fixed.param.cov <- fixed.param[idx.cov]
fixed.param.gev <- fixed.param[-idx.cov]
if (print.start.values)
cat("Computing appropriate starting values\n")
if (length(fixed.param.cov) > 0){
args <- c(list(data = data, coord = coord, cov.mod = cov.mod,
marge = "emp"), fixed.param.cov)
cov.param <- do.call("fitcovariance", args)$fitted
}
else
cov.param <- fitcovariance(data, coord, cov.mod, marge = "emp")$fitted
args <- c(list(data = data, covariables = as.matrix(covariables), loc.form = loc.form,
scale.form = scale.form, shape.form = shape.form,
method = method, warn = FALSE), fixed.param.gev)
spatgev <- do.call("fitspatgev", args)
frech <- data
gev <- predict(spatgev)
for (i in 1:n.site)
frech[,i] <- gev2frech(frech[,i], gev[i,"loc"], gev[i,"scale"], gev[i,"shape"])
sigma2param <- rep(0, length(sigma2.names))
names(sigma2param) <- sigma2.names
args <- c(list(data = frech, coord = coord, cov.mod = cov.mod, fit.marge = FALSE,
sigma2.form = sigma2.form, warn = FALSE, method = method, start =
c(as.list(sigma2param), as.list(cov.param))),
fixed.param.cov)
cov.param <- do.call("nsgeomgaussfull", args)
start <- c(as.list(cov.param$param), as.list(spatgev$param))
if (print.start.values){
cat("Starting values are defined\n")
cat("Starting values are:\n")
print(c(cov.param$fitted, spatgev$fitted))
}
return(start)
}
.start.brownresnick <- function(data, coord, covariables, loc.form, scale.form,
shape.form, print.start.values = TRUE,
method = "Nelder", ...){
n.site <- ncol(data)
param <- c("range", "smooth")
fixed.param <- list(...)[names(list(...)) %in% param]
idx.cov <- which(names(fixed.param) %in% param)
fixed.param.cov <- fixed.param[idx.cov]
fixed.param.gev <- fixed.param[-idx.cov]
if (print.start.values)
cat("Computing appropriate starting values\n")
if (length(fixed.param.cov) > 0){
args <- c(list(data = data, coord = coord, cov.mod = "brown",
marge = "emp"), fixed.param.cov)
cov.param <- do.call("fitcovariance", args)$fitted
}
else
cov.param <- fitcovariance(data, coord, "brown", marge = "emp")$fitted
args <- c(list(data = data, covariables = as.matrix(covariables), loc.form = loc.form,
scale.form = scale.form, shape.form = shape.form,
method = method, warn = FALSE), fixed.param.gev)
spatgev <- do.call("fitspatgev", args)
frech <- data
gev <- predict(spatgev)
for (i in 1:n.site)
frech[,i] <- gev2frech(frech[,i], gev[i,"loc"], gev[i,"scale"], gev[i,"shape"])
args <- c(list(data = frech, coord = coord, fit.marge = FALSE,
start = as.list(cov.param), warn = FALSE, method = method), fixed.param.cov)
cov.param <- do.call("brownresnickfull", args)
start <- c(as.list(cov.param$param), as.list(spatgev$param))
if (print.start.values){
cat("Starting values are defined\n")
cat("Starting values are:\n")
print(c(cov.param$fitted, spatgev$fitted))
}
return(start)
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.