#' print.ofit
#'
#' @param x Object of type `ofit`
#' @param ... Generic parameters to pass on.
#'
#' @return
#' No return value.
#'
#' @export
print.ofit <- function (x, ...) {
summary(x, ...)
}
#' summary.ofit
#'
#' @param object Object of type `ofit`
#' @param ... Generic parameters to pass on.
#'
#' @return
#' No return value.
#'
#' @export
summary.ofit <- function (object, ...) {
fit <- object
kappa <- fit$kappa
mu <- fit$mu
t1 <- fit$t1
t2 <- fit$t2
fit.mass <- abs(fit$fitresult$par[3])
fit.fpi <- 2*kappa*2*mu/sqrt(2)*abs(fit$fitresult$par[1])/sqrt(fit.mass^3)
fit.chisqr <- fit$fitresult$value
fit.dof <- length(fit$fitdata$t)-length(fit$fitresult$par)
cat("mu = ", mu, "\n")
cat("kappa = ", kappa, "\n")
cat("Nr of measurements = ", fit$N, "\n")
cat("No of replica = ", length(fit$nrep), "\n")
cat("no or measurements per replicum: ", fit$nrep, "\n")
cat("fitrange = ", t1, "-", t2, "\n")
cat("chi^2 = ", fit.chisqr, "\n")
cat("dof = ", fit.dof, "\n")
cat("chi^2/dof = ", fit.chisqr/fit.dof, "\n")
cat("\nmass = ", fit.mass, "\n")
cat("mpcac = ", fit.mass*fit$fitresult$par[2]/fit$fitresult$par[1]/2., "\n")
cat("\nP_L = ", fit$fitresult$par[1], "\n")
cat("A_L = ", fit$fitresult$par[2], "\n")
if(!is.null(fit$uwerrresultmps)) {
cat("\n--- Autocorrelation analysis for m_ps ---\n")
cat("\nS = ", fit$uwerrresultmps$S, "\n")
cat("mass = ", fit$uwerrresultmps$value[1], "\n")
cat("dmass = ", fit$uwerrresultmps$dvalue[1], "\n")
cat("ddmass = ", fit$uwerrresultmps$ddvalue[1], "\n")
cat("tauint = ", fit$uwerrresultmps$tauint[1], "\n")
cat("dtauint = ", fit$uwerrresultmps$dtauint[1], "\n")
cat("Wopt = ", fit$uwerrresultmps$Wopt[[1]], "\n")
if(fit$uwerrresultmps$R>1) {
cat("Qval =", fit$uwerrresultmps$Qval[1], "\n")
}
}
if(!is.null(fit$uwerrresultfps)) {
cat("\n--- Autocorrelation analysis for f_ps ---\n")
cat("\nS = ", fit$uwerrresultfps$S, "\n")
cat("fps = ", fit$uwerrresultfps$value[1]*2*kappa*2*mu/sqrt(2), "\n")
cat("dfps = ", fit$uwerrresultfps$dvalue[1]*2*kappa*2*mu/sqrt(2), "\n")
cat("ddfps = ", fit$uwerrresultfps$ddvalue[1]*2*kappa*2*mu/sqrt(2), "\n")
cat("tauint = ", fit$uwerrresultfps$tauint[1], "\n")
cat("dtauint = ", fit$uwerrresultfps$dtauint[1], "\n")
cat("Wopt = ", fit$uwerrresultfps$Wopt[[1]], "\n")
if(fit$uwerrresultfps$R>1) {
cat("Qval =", fit$uwerrresultfps$Qval[1], "\n")
}
}
if(!is.null(fit$uwerrresultmpcac)) {
cat("\n--- Autocorrelation analysis for m_pcac ---\n")
cat("\nS = ", fit$uwerrresultmpcac$S, "\n")
cat("mpcac = ", fit$uwerrresultmpcac$value[1], "\n")
cat("dmpcac = ", fit$uwerrresultmpcac$dvalue[1], "\n")
cat("ddmpcac = ", fit$uwerrresultmpcac$ddvalue[1], "\n")
cat("tauint = ", fit$uwerrresultmpcac$tauint[1], "\n")
cat("dtauint = ", fit$uwerrresultmpcac$dtauint[1], "\n")
cat("Wopt = ", fit$uwerrresultmpcac$Wopt[[1]], "\n")
if(fit$uwerrresultmpcac$R>1) {
cat("Qval =", fit$uwerrresultmpcac$Qval[1], "\n")
}
}
if(!is.null(fit$boot)) {
cat("--- Bootstrap analysis ---\n")
cat("---", fit$boot$R, "samples ---\n")
cat(" mean -err +err stderr bias\n")
fit$boot.ci <- boot::boot.ci(fit$boot, type = c("norm"), index=1)
cat("mpi = ", fit$boot$t0[1], "(", (fit$boot.ci$normal[1,2]-fit$boot$t0[1])/1.96
, ",", -(fit$boot$t0[1]-fit$boot.ci$normal[1,3])/1.96, ")", sd(fit$boot$t[,1]),
mean(fit$boot$t[,1])-fit$boot$t0[1],"\n")
# fit$boot.ci <- boot::boot.ci(fit$boot, type = c("norm"), index=2)
# cat("fpi = ", fit$boot$t0[2], "(", (fit$boot.ci$normal[1,2]-fit$boot$t0[2])/1.96
# , ",", -(fit$boot$t0[2]-fit$boot.ci$normal[1,3])/1.96, ")", sd(fit$boot$t[,2]),
# mean(fit$boot$t[,2])-fit$boot$t0[2], "\n")
fit$boot.ci <- boot::boot.ci(fit$boot, type = c("norm"), index=2)
cat("mpcac = ", fit$boot$t0[2], "(", (fit$boot.ci$normal[1,2]-fit$boot$t0[2])/1.96
, ",", -(fit$boot$t0[2]-fit$boot.ci$normal[1,3])/1.96, ")", sd(fit$boot$t[,2]),
mean(fit$boot$t[,2])-fit$boot$t0[2], "\n")
fit$boot.ci <- boot::boot.ci(fit$boot, type = c("norm"), index=3)
cat("P_L = ", fit$boot$t0[3], "(", (fit$boot.ci$normal[1,2]-fit$boot$t0[3])/1.96
, ",", -(fit$boot$t0[3]-fit$boot.ci$normal[1,3])/1.96, ")", sd(fit$boot$t[,3]),
mean(fit$boot$t[,3])-fit$boot$t0[3], "\n")
fit$boot.ci <- boot::boot.ci(fit$boot, type = c("norm"), index=4)
cat("A_L = ", fit$boot$t0[4], "(", (fit$boot.ci$normal[1,2]-fit$boot$t0[4])/1.96
, ",", -(fit$boot$t0[4]-fit$boot.ci$normal[1,3])/1.96, ")", sd(fit$boot$t[,4]),
mean(fit$boot$t[,4])-fit$boot$t0[4],"\n")
}
if(!is.null(fit$tsboot)) {
cat("\n--- Bootstrap analysis with blocking ---\n")
cat("---", fit$boot$R, "samples ---\n")
cat("--- block size", fit$tsboot$l, "---\n")
fit$tsboot.ci <- boot::boot.ci(fit$tsboot, type = c("norm"), index=1)
cat("mpi = ", fit$tsboot$t0[1], "(", (fit$tsboot.ci$normal[1,2]-fit$tsboot$t0[1])/1.96
, ",", -(fit$tsboot$t0[1]-fit$tsboot.ci$normal[1,3])/1.96, ")", sd(fit$tsboot$t[,1]),
mean(fit$tsboot$t[,1])-fit$tsboot$t0[1], "\n")
# fit$tsboot.ci <- boot::boot.ci(fit$tsboot, type = c("norm"), index=2)
# cat("fpi = ", fit$tsboot$t0[2], "(", (fit$tsboot.ci$normal[1,2]-fit$tsboot$t0[2])/1.96
# , ",", -(fit$tsboot$t0[2]-fit$tsboot.ci$normal[1,3])/1.96, ")", sd(fit$tsboot$t[,2]),
# mean(fit$tsboot$t[,2])-fit$tsboot$t0[2], "\n")
fit$tsboot.ci <- boot::boot.ci(fit$tsboot, type = c("norm"), index=2)
cat("mpcac = ", fit$tsboot$t0[2], "(", (fit$tsboot.ci$normal[1,2]-fit$tsboot$t0[2])/1.96
, ",", -(fit$tsboot$t0[2]-fit$tsboot.ci$normal[1,3])/1.96, ")", sd(fit$tsboot$t[,2]),
mean(fit$tsboot$t[,2])-fit$tsboot$t0[2], "\n")
fit$tsboot.ci <- boot::boot.ci(fit$tsboot, type = c("norm"), index=3)
cat("P_L = ", fit$tsboot$t0[3], "(", (fit$tsboot.ci$normal[1,2]-fit$tsboot$t0[3])/1.96
, ",", -(fit$tsboot$t0[3]-fit$tsboot.ci$normal[1,3])/1.96, ")", sd(fit$tsboot$t[,3]),
mean(fit$tsboot$t[,3])-fit$tsboot$t0[3], "\n")
fit$tsboot.ci <- boot::boot.ci(fit$tsboot, type = c("norm"), index=4)
cat("A_L = ", fit$tsboot$t0[4], "(", (fit$tsboot.ci$normal[1,2]-fit$tsboot$t0[4])/1.96
, ",", -(fit$tsboot$t0[4]-fit$tsboot.ci$normal[1,3])/1.96, ")", sd(fit$tsboot$t[,4]),
mean(fit$tsboot$t[,4])-fit$tsboot$t0[4], "\n")
}
}
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