Nothing
ntfact <- function(alpha=0.05,mswd=NULL,df=NULL){
if (is.null(mswd)){
if (is.null(df)){
out <- stats::qnorm(1-alpha/2)
} else if (df>0){
out <- stats::qt(1-alpha/2,df=df)
}
} else if (mswd$df>0){
out <- stats::qt(1-alpha/2,df=mswd$df)*sqrt(mswd$mswd)
} else {
out <- stats::qnorm(1-alpha/2)
}
out
}
inflate <- function(fit){
if (is.null(fit$model)) fit$model <- 1
(fit$model==1) && (fit$p.value<alpha())
}
#' @title Confidence intervals
#' @description Given a parameter estimate and its standard error,
#' calculate the corresponding 1-sigma, 2-sigma or
#' \eqn{100(1-\alpha)\%} confidence interval, in absolute or
#' relative units.
#' @param x scalar estimate
#' @param sx scalar or vector with the standard error of x without and
#' (optionally) with \eqn{\sqrt{MSWD}} overdispersion multiplier.
#' @param oerr indicates if the confidence intervals should be
#' reported as:
#'
#' \code{1}: 1\eqn{\sigma} absolute uncertainties.
#'
#' \code{2}: 2\eqn{\sigma} absolute uncertainties.
#'
#' \code{3}: absolute (1-\eqn{\alpha})\% confidence intervals, where
#' \eqn{\alpha} equales the value that is stored in
#' \code{settings('alpha')}.
#'
#' \code{4}: 1\eqn{\sigma} relative uncertainties (\eqn{\%}).
#'
#' \code{5}: 2\eqn{\sigma} relative uncertainties (\eqn{\%}).
#'
#' \code{6}: relative (1-\eqn{\alpha})\% confidence intervals, where
#' \eqn{\alpha} equales the value that is stored in
#' \code{settings('alpha')}.
#'
#' @param df (optional) number of degrees of freedom. Only used if
#' \code{sx} is a vector.
#' @param absolute logical. Returns absolute uncertainties even if
#' \code{oerr} is greater than 3. Used for some internal
#' \code{IsoplotR} functions.
#' @return A scalar or vector of the same size as \code{sx}.
#' @details Several of \code{IsoplotR}'s plotting functions (including
#' \code{\link{isochron}}, \code{\link{weightedmean}},
#' \code{\link{concordia}}, \code{\link{radialplot}} and
#' \code{\link{helioplot}}) return lists of parameters and their
#' standard errors. For `model-1' fits, if the data pass a
#' Chi-square test of homogeneity, then just one estimate for the
#' standard error is reported. This estimate can be converted to
#' a confidence interval by multiplication with the appropriate
#' quantile of a Normal distribution. Datasets that fail the
#' Chi-square test are said to be `overdispersed' with respect to
#' the analytical uncertainties. The simplest way (`model-1') to
#' deal with overdispersion is to inflate the standard error with
#' a \eqn{\sqrt{MSWD}} premultiplier. In this case,
#' \code{IsoplotR} returns two estimates of the standard error.
#' To convert the second estimate to a confidence interval
#' requires multiplication with the desired quantile of a
#' t-distribution with the appropriate degrees of freedom.
#' @examples
#' attach(examples)
#' fit <- isochron(PbPb,plot=FALSE,exterr=FALSE)
#' err <- ci(x=fit$age[1],sx=fit$age[-1],oerr=5,df=fit$df)
#' message('age=',signif(fit$age[1],4),'Ma, ',
#' '2se=',signif(err[1],2),'%, ',
#' '2se(with dispersion)=',signif(err[2],2),'%')
#' @export
ci <- function(x=0,sx,oerr=3,df=NULL,absolute=FALSE){
fact <- rep(ntfact(alpha()),length(sx))
if (!is.null(df) && df>0){
fact[-1] <- stats::qt(1-alpha()/2,df=df)
}
if (oerr>3 & absolute) oerr <- oerr-3
if (oerr==1) out <- sx
else if (oerr==2) out <- 2*sx
else if (oerr==3) out <- fact*sx
else if (oerr==4) out <- abs(100*sx/x)
else if (oerr==5) out <- abs(200*sx/x)
else if (oerr==6) out <- abs(100*fact*sx/x)
else stop('Illegal oerr value')
out
}
errlabelswapper <- function(errnames){
if (any(grepl('s\\[',errnames))){
out <- gsub('s\\[','err\\[',errnames)
} else {
out <- errnames
}
out
}
#' Formats table or vector of ages and errors
#' @param x an IsoplotR data object
#' @noRd
agerr <- function(x,...){ UseMethod("agerr",x) }
#' @param oerr output error (1:4 for 1 or 2 sigma, absolute or relative)
#' @param sigdig number of significant digits
#' @noRd
agerr.default <- function(x,oerr=1,sigdig=NA,...){
out <- tst <- x
tst[2] <- ci(x=x[1],sx=x[2],oerr=oerr)
out <- roundit(age=tst[1],err=tst[2],sigdig=sigdig)
names(out) <- names(tst) <- errlabelswapper(names(x))
out
}
#' @noRd
agerr.matrix <- function(x,oerr=1,sigdig=NA,...){
out <- tst <- x
nc <- ncol(x)
i <- seq(from=2,to=nc,by=2)
tst[,i] <- ci(x=x[,i-1],sx=x[,i],oerr=oerr)
if (is.na(sigdig)){
out <- tst
} else {
rounded <- roundit(age=tst[,i-1,drop=FALSE],
err=tst[,i,drop=FALSE],sigdig=sigdig)
out[,i-1] <- rounded[,1:(nc/2)]
out[,i] <- rounded[,(nc/2+1):nc]
if (nc%%2==1) out[,nc] <- signif(tst[,nc],digits=sigdig)
}
colnames(out) <- errlabelswapper(colnames(x))
out
}
# get significance level for error ellipses
oerr2alpha <- function(oerr=1){
if (oerr%in%c(1,4)) out <- stats::pnorm(-1)*2
else if (oerr%in%c(2,5)) out <- stats::pnorm(-2)*2
else out <- alpha()
out
}
maintit <- function(x,sx,n=NULL,ntit=paste0('(n=',n,')'),sigdig=2,
oerr=3,units=' Ma',prefix='age =',df=NULL){
xerr <- ci(x,sx,oerr=oerr,df=df)
rounded <- roundit(x,xerr,sigdig=sigdig,oerr=oerr,text=TRUE)
dispersed <- (length(sx)>1)
lst <- list(p=prefix,a=rounded[1],b=rounded[2],u=units,n=ntit)
if (dispersed){
lst$c <- rounded[3]
if (oerr>3){
out <- substitute(p~a*u%+-%b~'|'~c*'%'~n,lst)
} else {
out <- substitute(p~a%+-%b~'|'~c*u~n,lst)
}
} else {
if (oerr>3){
out <- substitute(p~a*u%+-%b*'%'~n,lst)
} else {
out <- substitute(p~a%+-%b*u~n,lst)
}
}
out
}
mswdtit <- function(mswd,p,sigdig=2){
substitute('MSWD ='~a*', p('*chi^2*') ='~b,
list(a=signif(mswd,sigdig),b=signif(p,sigdig)))
}
disptit <- function(w,sw,sigdig=2,oerr=3,units='',prefix='dispersion ='){
if (w>0){
if (identical(units,'%')) {
werr <- ci(100*w,100*sw,oerr=oerr,absolute=TRUE)
rounded <- roundit(100*w,werr,sigdig=sigdig,text=TRUE)
} else {
werr <- ci(w,sw,oerr=oerr)
rounded <- roundit(w,werr,sigdig=sigdig,oerr=oerr,text=TRUE)
}
} else {
w <- 0
werr <- NA
rounded <- c(w,werr)
}
lst <- list(p=prefix,a=rounded[1],b=rounded[2],u=units)
if (oerr>3){
out <- substitute(p~a*u%+-%b*'%',lst)
} else {
out <- substitute(p~a%+-%b*u,lst)
}
out
}
peaktit <- function(x,sx,p=NULL,sigdig=2,oerr=3,unit='Ma',prefix=NULL){
xerr <- ci(x,sx,oerr=oerr)
rounded.x <- roundit(x,xerr,sigdig=sigdig,oerr=oerr,text=TRUE)
if (is.null(p)){
lst <- list(p=prefix,a=rounded.x[1],b=rounded.x[2],u=unit)
if (oerr>3){
out <- substitute(p~a~u%+-%b,lst)
} else {
out <- substitute(p~a%+-%b~u,lst)
}
} else {
rounded.p <- signif(100*p,sigdig)
lst <- list(p=prefix,a=rounded.x[1],b=rounded.x[2],c=rounded.p[1],u=unit)
if (oerr>3){
out <- substitute(p~a~u%+-%b*'% (prop='*c*'%)',lst)
} else {
out <- substitute(p~a%+-%b~u~'(prop='*c*'%)',lst)
}
}
out
}
bayestit <- function(x,XL,n=NULL,ntit=paste0('(n=',n,')'),
sigdig=2,oerr=3,units=' Ma',prefix='age ='){
if (oerr%in%c(1,4)){
lq <- -1
uq <- 1
} else if (oerr%in%c(2,5)){
lq <- -2
uq <- 2
} else if (oerr%in%c(3,6)){
lq <- stats::qnorm(alpha())
uq <- stats::qnorm(1-alpha())
}
cdf <- cumsum(XL[,'L'])/sum(XL[,'L'])
increasing <- which(diff(cdf)>1e-20)
ll <- stats::spline(x=cdf[increasing],y=XL[increasing,'x'],
xout=stats::pnorm(lq),method='hyman')
ul <- stats::spline(x=cdf[increasing],y=XL[increasing,'x'],
xout=stats::pnorm(uq),method='hyman')
le <- (x-ll$y)
ue <- (ul$y-x)
if (oerr>3) {
le <- 100*le/x
ue <- 100*ue/x
}
rounded <- roundit(x,c(ue,le),sigdig=sigdig,oerr=oerr,text=TRUE)
lst <- list(p=prefix,a=rounded[1],b=rounded[2],c=rounded[3],u=units,n=ntit)
if (oerr>3){
out <- substitute(p~a*u+b/-c*'%'~n,lst)
} else {
out <- substitute(p~a+b/-c*u~n,lst)
}
out
}
#' Get a sample size label for the plot title
#' @param x an IsoplotR data object or a data vector
#' @noRd
get_ntit <- function(x,...){
UseMethod("get_ntit",x)
}
#' @param m minimum cutoff. Values below this are removed from the
#' total sample size
#' @param M maximum cutoff. Valus above this are removed from the
#' total sample size
#' @noRd
get_ntit.default <- function(x,m=min(x,na.rm=TRUE),M=max(x,na.rm=TRUE),...){
ns <- length(x)
bad <- which(is.na(x) | x<m | x>M)
nisnan <- length(bad)
out <- '(n='
if (nisnan>0) out <- paste0(out,ns-nisnan,'/')
paste0(out,ns,')')
}
#' @noRd
get_ntit.fissiontracks <- function(x,...){
if (x$format<2){
out <- get_ntit.default(x$x[,'Ns'])
} else {
out <- get_ntit.default(x$Ns)
}
out
}
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.