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Data X:
2967 2892 2798 2823 2901 2918 3059 2427 3141 2909 2938 2397 2967 2892 2798 2823 2901 2918 3059 2427 3141 2909 3458 2397 2967 2892 2798 2823 2901 2918 3059 2427 3141 3024 3458 2397 2967 2892 2798 2823 2901 2918 3059 2427 3100 3024 3458 2397 2967 2892 2798 2823 2901 2918 3059 2904 3100 3024 3458 2397 2967 2892 2798 2823 2901 2918 3056 2904 3100 3024 3458 2397 2967 2892 2798 2823 2901 2771 3056 2904 3100 3024 3458 2397 2967 2892 2798 2823 2897 2771 3056 2904 3100 3024 3458 2397 2967 2892 2798 2772 2897 2771 3056 2904 3100 3024 3458 2397 2967 2892 2857 2772 2897 2771 3056 2904 3100 3024 3458 2397 2967 3020 2857 2772 2897 2771 3056 2904 3100 3024 3458 2397 2648 3020 2857 2772 2897 2771 3056 2904 3100 3024 3458 2364 2648 3020 2857 2772 2897 2771 3056 2904 3100 3024 3194 2364 2648 3020 2857 2772 2897 2771 3056 2904 3100 3013 3194 2364 2648 3020 2857 2772 2897 2771 3056 2904 2560 3013 3194 2364 2648 3020 2857 2772 2897 2771 3056 3074 2560 3013 3194 2364 2648 3020 2857 2772 2897 2771 2746 3074 2560 3013 3194 2364 2648 3020 2857 2772 2897 2846 2746 3074 2560 3013 3194 2364 2648 3020 2857 2772 3184 2846 2746 3074 2560 3013 3194 2364 2648 3020 2857 2354 3184 2846 2746 3074 2560 3013 3194 2364 2648 3020 3080 2354 3184 2846 2746 3074 2560 3013 3194 2364 2648 2963 3080 2354 3184 2846 2746 3074 2560 3013 3194 2364 2430 2963 3080 2354 3184 2846 2746 3074 2560 3013 3194 2296 2430 2963 3080 2354 3184 2846 2746 3074 2560 3013 2416 2296 2430 2963 3080 2354 3184 2846 2746 3074 2560 2647 2416 2296 2430 2963 3080 2354 3184 2846 2746 3074 2789 2647 2416 2296 2430 2963 3080 2354 3184 2846 2746 2685 2789 2647 2416 2296 2430 2963 3080 2354 3184 2846 2666 2685 2789 2647 2416 2296 2430 2963 3080 2354 3184 2882 2666 2685 2789 2647 2416 2296 2430 2963 3080 2354 2953 2882 2666 2685 2789 2647 2416 2296 2430 2963 3080 2127 2953 2882 2666 2685 2789 2647 2416 2296 2430 2963 2563 2127 2953 2882 2666 2685 2789 2647 2416 2296 2430 3061 2563 2127 2953 2882 2666 2685 2789 2647 2416 2296 2809 3061 2563 2127 2953 2882 2666 2685 2789 2647 2416 2861 2809 3061 2563 2127 2953 2882 2666 2685 2789 2647 2781 2861 2809 3061 2563 2127 2953 2882 2666 2685 2789 2555 2781 2861 2809 3061 2563 2127 2953 2882 2666 2685 3206 2555 2781 2861 2809 3061 2563 2127 2953 2882 2666 2570 3206 2555 2781 2861 2809 3061 2563 2127 2953 2882 2410 2570 3206 2555 2781 2861 2809 3061 2563 2127 2953 3195 2410 2570 3206 2555 2781 2861 2809 3061 2563 2127 2736 3195 2410 2570 3206 2555 2781 2861 2809 3061 2563 2743 2736 3195 2410 2570 3206 2555 2781 2861 2809 3061 2934 2743 2736 3195 2410 2570 3206 2555 2781 2861 2809 2668 2934 2743 2736 3195 2410 2570 3206 2555 2781 2861 2907 2668 2934 2743 2736 3195 2410 2570 3206 2555 2781 2866 2907 2668 2934 2743 2736 3195 2410 2570 3206 2555 2983 2866 2907 2668 2934 2743 2736 3195 2410 2570 3206 2878 2983 2866 2907 2668 2934 2743 2736 3195 2410 2570 3225 2878 2983 2866 2907 2668 2934 2743 2736 3195 2410 2515 3225 2878 2983 2866 2907 2668 2934 2743 2736 3195 3193 2515 3225 2878 2983 2866 2907 2668 2934 2743 2736 2663 3193 2515 3225 2878 2983 2866 2907 2668 2934 2743 2908 2663 3193 2515 3225 2878 2983 2866 2907 2668 2934 2896 2908 2663 3193 2515 3225 2878 2983 2866 2907 2668 2853 2896 2908 2663 3193 2515 3225 2878 2983 2866 2907 3028 2853 2896 2908 2663 3193 2515 3225 2878 2983 2866 3053 3028 2853 2896 2908 2663 3193 2515 3225 2878 2983 2455 3053 3028 2853 2896 2908 2663 3193 2515 3225 2878 3401 2455 3053 3028 2853 2896 2908 2663 3193 2515 3225 2969 3401 2455 3053 3028 2853 2896 2908 2663 3193 2515 3243 2969 3401 2455 3053 3028 2853 2896 2908 2663 3193 2849 3243 2969 3401 2455 3053 3028 2853 2896 2908 2663 3296 2849 3243 2969 3401 2455 3053 3028 2853 2896 2908 3121 3296 2849 3243 2969 3401 2455 3053 3028 2853 2896 3194 3121 3296 2849 3243 2969 3401 2455 3053 3028 2853 3023 3194 3121 3296 2849 3243 2969 3401 2455 3053 3028 2984 3023 3194 3121 3296 2849 3243 2969 3401 2455 3053 3525 2984 3023 3194 3121 3296 2849 3243 2969 3401 2455 3116 3525 2984 3023 3194 3121 3296 2849 3243 2969 3401 2383 3116 3525 2984 3023 3194 3121 3296 2849 3243 2969 3294 2383 3116 3525 2984 3023 3194 3121 3296 2849 3243 2882 3294 2383 3116 3525 2984 3023 3194 3121 3296 2849 2820 2882 3294 2383 3116 3525 2984 3023 3194 3121 3296 2583 2820 2882 3294 2383 3116 3525 2984 3023 3194 3121 2803 2583 2820 2882 3294 2383 3116 3525 2984 3023 3194 2767 2803 2583 2820 2882 3294 2383 3116 3525 2984 3023 2945 2767 2803 2583 2820 2882 3294 2383 3116 3525 2984 2716 2945 2767 2803 2583 2820 2882 3294 2383 3116 3525 2644 2716 2945 2767 2803 2583 2820 2882 3294 2383 3116 2956 2644 2716 2945 2767 2803 2583 2820 2882 3294 2383 2598 2956 2644 2716 2945 2767 2803 2583 2820 2882 3294 2171 2598 2956 2644 2716 2945 2767 2803 2583 2820 2882 2994 2171 2598 2956 2644 2716 2945 2767 2803 2583 2820 2645 2994 2171 2598 2956 2644 2716 2945 2767 2803 2583 2724 2645 2994 2171 2598 2956 2644 2716 2945 2767 2803 2550 2724 2645 2994 2171 2598 2956 2644 2716 2945 2767 2707 2550 2724 2645 2994 2171 2598 2956 2644 2716 2945 2679 2707 2550 2724 2645 2994 2171 2598 2956 2644 2716 2878 2679 2707 2550 2724 2645 2994 2171 2598 2956 2644 2307 2878 2679 2707 2550 2724 2645 2994 2171 2598 2956 2496 2307 2878 2679 2707 2550 2724 2645 2994 2171 2598 2637 2496 2307 2878 2679 2707 2550 2724 2645 2994 2171 2436 2637 2496 2307 2878 2679 2707 2550 2724 2645 2994 2426 2436 2637 2496 2307 2878 2679 2707 2550 2724 2645 2607 2426 2436 2637 2496 2307 2878 2679 2707 2550 2724 2533 2607 2426 2436 2637 2496 2307 2878 2679 2707 2550 2888 2533 2607 2426 2436 2637 2496 2307 2878 2679 2707 2520 2888 2533 2607 2426 2436 2637 2496 2307 2878 2679 2229 2520 2888 2533 2607 2426 2436 2637 2496 2307 2878 2804 2229 2520 2888 2533 2607 2426 2436 2637 2496 2307 2661 2804 2229 2520 2888 2533 2607 2426 2436 2637 2496 2547 2661 2804 2229 2520 2888 2533 2607 2426 2436 2637 2509 2547 2661 2804 2229 2520 2888 2533 2607 2426 2436 2465 2509 2547 2661 2804 2229 2520 2888 2533 2607 2426 2629 2465 2509 2547 2661 2804 2229 2520 2888 2533 2607 2706 2629 2465 2509 2547 2661 2804 2229 2520 2888 2533 2666 2706 2629 2465 2509 2547 2661 2804 2229 2520 2888 2432 2666 2706 2629 2465 2509 2547 2661 2804 2229 2520 2836 2432 2666 2706 2629 2465 2509 2547 2661 2804 2229 2888 2836 2432 2666 2706 2629 2465 2509 2547 2661 2804 2566 2888 2836 2432 2666 2706 2629 2465 2509 2547 2661 2802 2566 2888 2836 2432 2666 2706 2629 2465 2509 2547 2611 2802 2566 2888 2836 2432 2666 2706 2629 2465 2509 2683 2611 2802 2566 2888 2836 2432 2666 2706 2629 2465 2675 2683 2611 2802 2566 2888 2836 2432 2666 2706 2629 2434 2675 2683 2611 2802 2566 2888 2836 2432 2666 2706 2693 2434 2675 2683 2611 2802 2566 2888 2836 2432 2666 2619 2693 2434 2675 2683 2611 2802 2566 2888 2836 2432 2903 2619 2693 2434 2675 2683 2611 2802 2566 2888 2836 2550 2903 2619 2693 2434 2675 2683 2611 2802 2566 2888 2900 2550 2903 2619 2693 2434 2675 2683 2611 2802 2566 2456 2900 2550 2903 2619 2693 2434 2675 2683 2611 2802 2912 2456 2900 2550 2903 2619 2693 2434 2675 2683 2611 2883 2912 2456 2900 2550 2903 2619 2693 2434 2675 2683 2464 2883 2912 2456 2900 2550 2903 2619 2693 2434 2675 2655 2464 2883 2912 2456 2900 2550 2903 2619 2693 2434 2447 2655 2464 2883 2912 2456 2900 2550 2903 2619 2693 2592 2447 2655 2464 2883 2912 2456 2900 2550 2903 2619 2698 2592 2447 2655 2464 2883 2912 2456 2900 2550 2903 2274 2698 2592 2447 2655 2464 2883 2912 2456 2900 2550 2901 2274 2698 2592 2447 2655 2464 2883 2912 2456 2900 2397 2901 2274 2698 2592 2447 2655 2464 2883 2912 2456 3004 2397 2901 2274 2698 2592 2447 2655 2464 2883 2912 2614 3004 2397 2901 2274 2698 2592 2447 2655 2464 2883 2882 2614 3004 2397 2901 2274 2698 2592 2447 2655 2464 2671 2882 2614 3004 2397 2901 2274 2698 2592 2447 2655 2761 2671 2882 2614 3004 2397 2901 2274 2698 2592 2447 2806 2761 2671 2882 2614 3004 2397 2901 2274 2698 2592 2414 2806 2761 2671 2882 2614 3004 2397 2901 2274 2698 2673 2414 2806 2761 2671 2882 2614 3004 2397 2901 2274 2748 2673 2414 2806 2761 2671 2882 2614 3004 2397 2901 2112 2748 2673 2414 2806 2761 2671 2882 2614 3004 2397 2903 2112 2748 2673 2414 2806 2761 2671 2882 2614 3004 2633 2903 2112 2748 2673 2414 2806 2761 2671 2882 2614 2684 2633 2903 2112 2748 2673 2414 2806 2761 2671 2882 2861 2684 2633 2903 2112 2748 2673 2414 2806 2761 2671 2504 2861 2684 2633 2903 2112 2748 2673 2414 2806 2761 2708 2504 2861 2684 2633 2903 2112 2748 2673 2414 2806 2961 2708 2504 2861 2684 2633 2903 2112 2748 2673 2414 2535 2961 2708 2504 2861 2684 2633 2903 2112 2748 2673 2688 2535 2961 2708 2504 2861 2684 2633 2903 2112 2748 2699 2688 2535 2961 2708 2504 2861 2684 2633 2903 2112 2469 2699 2688 2535 2961 2708 2504 2861 2684 2633 2903 2585 2469 2699 2688 2535 2961 2708 2504 2861 2684 2633 2582 2585 2469 2699 2688 2535 2961 2708 2504 2861 2684 2480 2582 2585 2469 2699 2688 2535 2961 2708 2504 2861 2709 2480 2582 2585 2469 2699 2688 2535 2961 2708 2504 2441 2709 2480 2582 2585 2469 2699 2688 2535 2961 2708 2182 2441 2709 2480 2582 2585 2469 2699 2688 2535 2961 2585 2182 2441 2709 2480 2582 2585 2469 2699 2688 2535 2881 2585 2182 2441 2709 2480 2582 2585 2469 2699 2688 2422 2881 2585 2182 2441 2709 2480 2582 2585 2469 2699 2690 2422 2881 2585 2182 2441 2709 2480 2582 2585 2469 2659 2690 2422 2881 2585 2182 2441 2709 2480 2582 2585 2535 2659 2690 2422 2881 2585 2182 2441 2709 2480 2582 2613 2535 2659 2690 2422 2881 2585 2182 2441 2709 2480
Names of X columns:
Y Y1 Y2 Y3 Y4 y5 y6 y7 y78 y9 y10
Sample Range:
(leave blank to include all observations)
From:
To:
Column Number of Endogenous Series
(?)
Fixed Seasonal Effects
Include Monthly Dummies
Do not include Seasonal Dummies
Include Seasonal Dummies
Type of Equation
Linear Trend
No Linear Trend
Linear Trend
First Differences
Seasonal Differences (s)
First and Seasonal Differences (s)
Degree of Predetermination (lagged endogenous variables)
Degree of Seasonal Predetermination
Seasonality
12
1
2
3
4
5
6
7
8
9
10
11
12
Chart options
R Code
library(lattice) library(lmtest) n25 <- 25 #minimum number of obs. for Goldfeld-Quandt test par1 <- as.numeric(par1) x <- t(y) k <- length(x[1,]) n <- length(x[,1]) x1 <- cbind(x[,par1], x[,1:k!=par1]) mycolnames <- c(colnames(x)[par1], colnames(x)[1:k!=par1]) colnames(x1) <- mycolnames #colnames(x)[par1] x <- x1 if (par3 == 'First Differences'){ x2 <- array(0, dim=c(n-1,k), dimnames=list(1:(n-1), paste('(1-B)',colnames(x),sep=''))) for (i in 1:n-1) { for (j in 1:k) { x2[i,j] <- x[i+1,j] - x[i,j] } } x <- x2 } if (par2 == 'Include Monthly Dummies'){ x2 <- array(0, dim=c(n,11), dimnames=list(1:n, paste('M', seq(1:11), sep =''))) for (i in 1:11){ x2[seq(i,n,12),i] <- 1 } x <- cbind(x, x2) } if (par2 == 'Include Quarterly Dummies'){ x2 <- array(0, dim=c(n,3), dimnames=list(1:n, paste('Q', seq(1:3), sep =''))) for (i in 1:3){ x2[seq(i,n,4),i] <- 1 } x <- cbind(x, x2) } k <- length(x[1,]) if (par3 == 'Linear Trend'){ x <- cbind(x, c(1:n)) colnames(x)[k+1] <- 't' } x k <- length(x[1,]) df <- as.data.frame(x) (mylm <- lm(df)) (mysum <- summary(mylm)) if (n > n25) { kp3 <- k + 3 nmkm3 <- n - k - 3 gqarr <- array(NA, dim=c(nmkm3-kp3+1,3)) numgqtests <- 0 numsignificant1 <- 0 numsignificant5 <- 0 numsignificant10 <- 0 for (mypoint in kp3:nmkm3) { j <- 0 numgqtests <- numgqtests + 1 for (myalt in c('greater', 'two.sided', 'less')) { j <- j + 1 gqarr[mypoint-kp3+1,j] <- gqtest(mylm, point=mypoint, alternative=myalt)$p.value } if (gqarr[mypoint-kp3+1,2] < 0.01) numsignificant1 <- numsignificant1 + 1 if (gqarr[mypoint-kp3+1,2] < 0.05) numsignificant5 <- numsignificant5 + 1 if (gqarr[mypoint-kp3+1,2] < 0.10) numsignificant10 <- numsignificant10 + 1 } gqarr } bitmap(file='test0.png') plot(x[,1], type='l', main='Actuals and Interpolation', ylab='value of Actuals and Interpolation (dots)', xlab='time or index') points(x[,1]-mysum$resid) grid() dev.off() bitmap(file='test1.png') plot(mysum$resid, type='b', pch=19, main='Residuals', ylab='value of Residuals', xlab='time or index') grid() dev.off() bitmap(file='test2.png') hist(mysum$resid, main='Residual Histogram', xlab='values of Residuals') grid() dev.off() bitmap(file='test3.png') densityplot(~mysum$resid,col='black',main='Residual Density Plot', xlab='values of Residuals') dev.off() bitmap(file='test4.png') qqnorm(mysum$resid, main='Residual Normal Q-Q Plot') qqline(mysum$resid) grid() dev.off() (myerror <- as.ts(mysum$resid)) bitmap(file='test5.png') dum <- cbind(lag(myerror,k=1),myerror) dum dum1 <- dum[2:length(myerror),] dum1 z <- as.data.frame(dum1) z plot(z,main=paste('Residual Lag plot, lowess, and regression line'), ylab='values of Residuals', xlab='lagged values of Residuals') lines(lowess(z)) abline(lm(z)) grid() dev.off() bitmap(file='test6.png') acf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Autocorrelation Function') grid() dev.off() bitmap(file='test7.png') pacf(mysum$resid, lag.max=length(mysum$resid)/2, main='Residual Partial Autocorrelation Function') grid() dev.off() bitmap(file='test8.png') opar <- par(mfrow = c(2,2), oma = c(0, 0, 1.1, 0)) plot(mylm, las = 1, sub='Residual Diagnostics') par(opar) dev.off() if (n > n25) { bitmap(file='test9.png') plot(kp3:nmkm3,gqarr[,2], main='Goldfeld-Quandt test',ylab='2-sided p-value',xlab='breakpoint') grid() dev.off() } load(file='createtable') a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Estimated Regression Equation', 1, TRUE) a<-table.row.end(a) myeq <- colnames(x)[1] myeq <- paste(myeq, '[t] = ', sep='') for (i in 1:k){ if (mysum$coefficients[i,1] > 0) myeq <- paste(myeq, '+', '') myeq <- paste(myeq, mysum$coefficients[i,1], sep=' ') if (rownames(mysum$coefficients)[i] != '(Intercept)') { myeq <- paste(myeq, rownames(mysum$coefficients)[i], sep='') if (rownames(mysum$coefficients)[i] != 't') myeq <- paste(myeq, '[t]', sep='') } } myeq <- paste(myeq, ' + e[t]') a<-table.row.start(a) a<-table.element(a, myeq) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable1.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,hyperlink('http://www.xycoon.com/ols1.htm','Multiple Linear Regression - Ordinary Least Squares',''), 6, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Variable',header=TRUE) a<-table.element(a,'Parameter',header=TRUE) a<-table.element(a,'S.D.',header=TRUE) a<-table.element(a,'T-STAT<br />H0: parameter = 0',header=TRUE) a<-table.element(a,'2-tail p-value',header=TRUE) a<-table.element(a,'1-tail p-value',header=TRUE) a<-table.row.end(a) for (i in 1:k){ a<-table.row.start(a) a<-table.element(a,rownames(mysum$coefficients)[i],header=TRUE) a<-table.element(a,mysum$coefficients[i,1]) a<-table.element(a, round(mysum$coefficients[i,2],6)) a<-table.element(a, round(mysum$coefficients[i,3],4)) a<-table.element(a, round(mysum$coefficients[i,4],6)) a<-table.element(a, round(mysum$coefficients[i,4]/2,6)) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable2.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Regression Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple R',1,TRUE) a<-table.element(a, sqrt(mysum$r.squared)) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'R-squared',1,TRUE) a<-table.element(a, mysum$r.squared) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Adjusted R-squared',1,TRUE) a<-table.element(a, mysum$adj.r.squared) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (value)',1,TRUE) a<-table.element(a, mysum$fstatistic[1]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (DF numerator)',1,TRUE) a<-table.element(a, mysum$fstatistic[2]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'F-TEST (DF denominator)',1,TRUE) a<-table.element(a, mysum$fstatistic[3]) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'p-value',1,TRUE) a<-table.element(a, 1-pf(mysum$fstatistic[1],mysum$fstatistic[2],mysum$fstatistic[3])) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Residual Statistics', 2, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Residual Standard Deviation',1,TRUE) a<-table.element(a, mysum$sigma) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Sum Squared Residuals',1,TRUE) a<-table.element(a, sum(myerror*myerror)) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable3.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a, 'Multiple Linear Regression - Actuals, Interpolation, and Residuals', 4, TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a, 'Time or Index', 1, TRUE) a<-table.element(a, 'Actuals', 1, TRUE) a<-table.element(a, 'Interpolation<br />Forecast', 1, TRUE) a<-table.element(a, 'Residuals<br />Prediction Error', 1, TRUE) a<-table.row.end(a) for (i in 1:n) { a<-table.row.start(a) a<-table.element(a,i, 1, TRUE) a<-table.element(a,x[i]) a<-table.element(a,x[i]-mysum$resid[i]) a<-table.element(a,mysum$resid[i]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable4.tab') if (n > n25) { a<-table.start() a<-table.row.start(a) a<-table.element(a,'Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'p-values',header=TRUE) a<-table.element(a,'Alternative Hypothesis',3,header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'breakpoint index',header=TRUE) a<-table.element(a,'greater',header=TRUE) a<-table.element(a,'2-sided',header=TRUE) a<-table.element(a,'less',header=TRUE) a<-table.row.end(a) for (mypoint in kp3:nmkm3) { a<-table.row.start(a) a<-table.element(a,mypoint,header=TRUE) a<-table.element(a,gqarr[mypoint-kp3+1,1]) a<-table.element(a,gqarr[mypoint-kp3+1,2]) a<-table.element(a,gqarr[mypoint-kp3+1,3]) a<-table.row.end(a) } a<-table.end(a) table.save(a,file='mytable5.tab') a<-table.start() a<-table.row.start(a) a<-table.element(a,'Meta Analysis of Goldfeld-Quandt test for Heteroskedasticity',4,TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'Description',header=TRUE) a<-table.element(a,'# significant tests',header=TRUE) a<-table.element(a,'% significant tests',header=TRUE) a<-table.element(a,'OK/NOK',header=TRUE) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'1% type I error level',header=TRUE) a<-table.element(a,numsignificant1) a<-table.element(a,numsignificant1/numgqtests) if (numsignificant1/numgqtests < 0.01) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'5% type I error level',header=TRUE) a<-table.element(a,numsignificant5) a<-table.element(a,numsignificant5/numgqtests) if (numsignificant5/numgqtests < 0.05) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.row.start(a) a<-table.element(a,'10% type I error level',header=TRUE) a<-table.element(a,numsignificant10) a<-table.element(a,numsignificant10/numgqtests) if (numsignificant10/numgqtests < 0.1) dum <- 'OK' else dum <- 'NOK' a<-table.element(a,dum) a<-table.row.end(a) a<-table.end(a) table.save(a,file='mytable6.tab') }
Compute
Summary of computational transaction
Raw Input
view raw input (R code)
Raw Output
view raw output of R engine
Computing time
1 seconds
R Server
Big Analytics Cloud Computing Center
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