Nothing
Seminaive=function(data,y.col,coords.col,covar,covar.col,copred,cov.model="exponential",thetaini,fix.nugget=TRUE,nugget,kappa=0,cons,MaxIter,cc,cutoff,trend){
if(!is.data.frame(data) & !is.numeric(data)) stop("data must be a data.frame or numeric matrix")
if(!is.data.frame(data)) data=as.data.frame(data)
if(!is.numeric(cutoff)) stop ("cutoff mus be a numeric vector")
if(!is.numeric(thetaini)) stop ("thetaini must be a numeric vector thetaini=(sigma2,phi)")
if(length(which(thetaini<0))>0) stop("all initials values for the covariance structure must be in [0,Inf)")
if(length(thetaini)!=2) stop("thetaini must contains the initials values for sigma2 and phi")
if(!is.numeric(kappa)) stop("kappa must be a real number in [0,Inf)")
if(kappa<0) stop("kappa must be a real number in [0,Inf)")
if(!is.numeric(nugget)) stop("kappa must be a real number in [0,Inf)")
if(nugget<0) stop("nugget must be a real number in [0,Inf)")
if(!is.logical(fix.nugget)) stop("fix.nugget must be TRUE or FALSE.")
if(!is.logical(covar)) stop(" covar must be TRUE or FALSE.")
if(nrow(data)!=nrow(cc)) stop ("data and cc does not have the same number of lines")
if(length(which(cc==1))< length(cutoff)) stop("Detections limits not coincide with the number of censored observations")
if (trend!='cte'& trend!='1st' & trend!="2nd" & !inherits(trend,'formula')) stop('trend is not valid (see trend.spatial from geoR)')
if(!is.numeric(y.col)) stop("a correct column for y (response) must be specified")
if((y.col%%1)!=0) stop("a correct column for y (response) must be specified")
if (sum(cc%in%c(0,1))< length(cc)) stop("The elements of the vector cc must be 0 or 1")
if(MaxIter <= 0 |MaxIter%%1!=0) stop("MaxIter must be a positive integer value")
if(sum(which(cons<0))>0) stop("all values in vector cons=(c1,c2,c3) must be positive")
if(length(cons)!=3) stop("cons must contains (c1,c2,c3) constants for the algorithm")
if(cov.model!="matern" & cov.model!="exponential" & cov.model!="gaussian" &cov.model!="spherical" &
cov.model!="circular" & cov.model!="cubic" & cov.model!="wave" & cov.model!="linear" &
cov.model!="power" &cov.model!="powered.exponential" &cov.model!="stable" & cov.model!="cauchy" &
cov.model!="gencauchy" &cov.model!="gneiting" &cov.model!="gneiting.matern" &cov.model!="pure.nugget") {
stop('cov.model should be one of matern, exponential, gaussian, spherical,
circular,cubic, wave, linear, power, powered.exponential, stable, cauchy, gencauchy,
gneiting, gneiting.matern, pure.nugget')
}
if(covar==T){
if(!is.numeric(covar.col)) stop("a correct columns for x (design matrix) must be specified")
div1=covar.col%%1
if(sum(which(div1!=0))>0) stop("a correct columns for x (design matrix) must be specified")
}
##validating NA
if(sum(is.na(data)) > 0) stop("There are some NA values in data")
if(sum(is.na(cc)) > 0) stop("There are some NA values in cc")
if(sum(is.na(copred)) > 0) stop("There are some NA values in copred")
if(sum(is.na(cutoff)) > 0) stop("There are some NA values in cutoff")
######Not data
y = data[,y.col]
coords = data[,coords.col]
if((length(y) == 0) | (length(cc) == 0)|(length(coords) == 0)|(length(copred) == 0)|(length(cutoff) == 0)){
stop("All parameters must be provided")}
if(covar==F){
if(inherits(trend,'formula')) stop("trend must be cte,1stor 2nd when covar=F")
}
out=suppressWarnings(seminaive(data=data,y.col=y.col,covar=covar,coords.col=coords.col,covar.col=covar.col,cov.model=cov.model,thetaini=thetaini,fix.nugget=fix.nugget,nugget=nugget,kappa=kappa,cons=cons,MaxIter=MaxIter,cc=cc,cutof=cutoff,copred=copred,trend=trend))
if(trend=="cte"){
trend1="Constant trend"
}
if(trend=="1st"){
trend1="Linear function of its coordinates,
mu = beta0 + beta1*CoordX + beta2*CoordY"
}
if(trend=="2nd"){
trend1="Linear function of its coordinates,
mu = beta0 + beta1*CoordX + beta2*CoordY + beta3*(CoordX)^2 +
+ beta4*(CoordY)^2 + beta5*(CoordX*CoordY)"
}
if(inherits(trend,'formula')){
trend1= "Linear trend,
mu = X*beta"
}
out$trend1=trend1
out$type=cov.model
class(out)="seminaive"
return(out)
}
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