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...# y-yhat ss <- sum(wconstant *res^2) s <- sqrt(ss/df) # r terms this residual standard error x0 <- x1[1] # focal x for first observation dist1 <- abs(x1 - x0) # distance from focal x h <- sort(dist1)[.4*length(x1)] # bandwidth for span: bandwidth = span*length(x1) inwindow <- dist1 <= h # observations within window d <- dist1[dist1 <= h] z <- d/h w1 <- (1-abs(z)^3)^3 w2 <- sum(w1^2) s*sqrt(w2) # calculated sefit > s*sqrt(w2) [1] 8.052887 this is quite high, and r gives me > predict(lo1, se=T)$se.fit[1] 1 0.6055714 alt...

...24, i32* %tmp8, align 1 store i32 0, i32* %tmp, align 4 %tmp9 = load i32* %tmp, align 4 ; <i32> [#uses=1] store i32 %tmp9, i32* %retval, align 4 br label %return return: ; preds = %entry %retval10 = load i32* %retval ; <i32> [#uses=1] ret i32 %retval10 } define void @foo(i8* %inWindow) nounwind { entry: %inWindow_addr = alloca i8* ; <i8**> [#uses=1] %"alloca point" = bitcast i32 0 to i32 ; <i32> [#uses=0] store i8* %inWindow, i8** %inWindow_addr %tmp = call i32 @bork( i32 (...)* bitcast (i32 ()* @hndlr to i32 (...)*), %struct.E* getelementptr ([1 x %...