Correct a bug in 'nlsJack' when the model was fitting using weighted least squares (issue #5)

Author: aursiber

NAMESPACE

@@ -2,7 +2,7 @@
 importFrom("stats", "coef", "confint", "df.residual", "fitted", "formula",
   "pnorm", "ppoints", "predict", "profile", "qf", "qnorm", 
   "qqline", "qqnorm", "qt", "quantile", "resid", "residuals",
-  "runif", "sd", "shapiro.test", "update", "vcov")
+  "runif", "sd", "shapiro.test", "update", "vcov", "weights")
 importFrom("grDevices", "terrain.colors")
 importFrom("graphics", "abline", "boxplot", "contour", "hist", "image",
   "layout", "lines", "par", "plot", "points", "text")

R/nlsJack.R

@@ -9,10 +9,14 @@
 	np <- length(coef(nls))
 
 	l1 <- lapply(1:nl, function(z){
-		nls2 <- update(nls, data=data[-z,], start=as.list(coef(nls)));
-		return(list(coef=coef(nls2), sigma=summary(nls2)$sigma, rss=sum(residuals(nls2)^2), dfb=abs(coef(nls2)-coef(nls))/(summary(nls)$parameters[,2])))
+	    if(!is.null(weights(nls))) {
+	        nls2 <- update(nls, data=data[-z,], weights= weights(nls)[-z], start=as.list(coef(nls)))
+	    } else {
+	        nls2 <- update(nls, data=data[-z,], start=as.list(coef(nls)))
+	    }
+	    return(list(coef=coef(nls2), sigma=summary(nls2)$sigma, rss=sum(residuals(nls2)^2), dfb=abs(coef(nls2)-coef(nls))/(summary(nls)$parameters[,2])))
 	})
-
+	
 	tabjack <- t(sapply(l1, function(z) z$coef))
 	rsejack <- sapply(l1, function(z) z$sigma)
 	rssjack <- sapply(l1, function(z) z$rss)