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calm <- function(data)
{
y <- data[[2]]
x <- data[[1]]
m <- lm(y ~ x)
s <- summary(m)
if (s$coefficients[1,4] > 0.05)
{
m <- lm(y ~ x - 1)
s <- summary(m)
m$intercept <- FALSE
} else {
m$intercept <- TRUE
}
class(m) <- "calm"
m$yname <- names(data)[[1]]
m$xname <- names(data)[[2]]
return(m)
}
predict.calm <- predict.lm
print.calm <- print.lm
summary.calm <- summary.lm
plot.calm <- function(x,...,
xunit="",yunit="",measurand="",
level=0.95)
{
m <- x
x <- m$model$x
y <- m$model$y
newdata <- data.frame(x = seq(0,max(x),length=250))
pred.lim <- predict(m, newdata, interval = "prediction",level=level)
conf.lim <- predict(m, newdata, interval = "confidence",level=level)
if (xunit!="") {
xlab <- paste("Concentration in ",xunit)
} else xlab <- m$xname
if (yunit=="") yunit <- m$yname
if (measurand!="") {
main <- paste("Calibration for",measurand)
} else main <- "Calibration"
plot(1,
xlab = xlab,
ylab = yunit,
type = "n",
main = main,
xlim = c(0,max(x)),
ylim = range(pred.lim)
)
points(x,y, pch = 21, bg = "yellow")
matlines(newdata$x, pred.lim, lty = c(1, 4, 4),
col = c("black", "red", "red"))
matlines(newdata$x, conf.lim, lty = c(1, 3, 3),
col = c("black", "green4", "green4"))
legend(min(x),
max(pred.lim, na.rm = TRUE),
legend = c("Fitted Line", "Confidence Bands",
"Prediction Bands"),
lty = c(1, 3, 4),
lwd = 2,
col = c("black", "green4", "red"),
horiz = FALSE, cex = 0.9, bg = "gray95")
}
predictx <- function(m,yobs,level=0.95)
{
s <- summary(m)
xi <- m$model$x
yi <- m$model$y
n <- length(yi)
p <- length(yobs)
if (p > 1) {
varyobs <- var(yobs)
} else {
varyobs <- 0
}
if (!m$intercept) {
b1 <- summary(m)$coef["x","Estimate"]
varb1 <- summary(m)$coef["x","Std. Error"]^2
xpred <- mean(yobs)/b1
varxpred <- (varyobs + xpred^2 * varb1) / b1^2
sdxpred <- sqrt(varxpred)
} else
{
b0 <- summary(m)$coef["(Intercept)","Estimate"]
b1 <- summary(m)$coef["x","Estimate"]
S <- summary(m)$sigma
xpred <- (mean(yobs) - b0)/b1
sumxxbar <- sum((xi - mean(xi))^2)
yybar <- (mean(yobs) - mean(yi))^2
sdxpred <- (S/b1) * (1/p + 1/n + yybar/(b1^2 * sumxxbar))^0.5
}
t <- qt((1 + level)/2,n - 2)
confxpred <- t * sdxpred
result <- c(estimate=xpred,sdxpred=sdxpred,confxpred=confxpred)
}
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