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...result.C) # concatenate result vectors variables[i] <- results } variables <- as.data.frame(t(as.matrix(variables))) # turn result vectors into a matrix, then transpose it and output as a data frame # add column and row names c.names <- c("ResultA", "ResultB", "ResultC") # set names for result vectors colnames(variables) <- c.names rownames(variables) <- filenames # export to csv file write.csv(variables, file="/Users/Desktop/Test.csv") # ----------------------------------------END R-CODE----------------------------------- -- View this mes...

I explain better: I have this percentage z<-1/(n*365) where n=20 so z is 0,000136986 Imagine: a matrix with length(n*365) so that matrix result is resultc( 1, 1-z result previous row-z result previous row-z .... 0) If I plot this is a linear decreasing line I want to plot an upper line wich is 10% higher tan resultc on the first values and then decreasing so that last value will be 0.05. the same in the lower, a line which values are at the beggin...

Hi all I want to add a band of fluctuaci?n (exponential decreading) to a linear deacrecing values Imagine: I have a matrix like c(10,9,8,7,6,5,4,3,2,1) The thing is I want two new lines so that the m?ximum value of the new colum on the m?ximum is from 10% to 5% higher and the same lower for the m?nimum the final two matix will be something like c(10+0.10*10,9+0.089*9,8+0.075*8.....,1+0.05*1)

...Sq F Pr(>F) 1 127 7.3782 2 137 7.6848 -10 -0.3066 0.5277 0.868 As I said, the results of the chisquare test with linear.hypothesis and the waldtest.systemfit coincide. I have one more problem. This is the output of lrtest.systemfit: lrtest.systemfit(resultc=adfResc,resultu=adfResu) Likelihood-Ratio-test for parameter restrictions in equation systems LR-statistic: degrees of freedom: p-value: Why do I get empty values? In summary, I need to understand why the two ftests give different results; why lrtest.systemfit gives empty output; is there so...

...<- par(mfrow = c(1, 2)) xyplot(x1+x2+x3 ~ y, data=resulta, type="l", pch=LETTERS[1:3], lty=c(1:3), main="For k=3, theata1=1") xyplot(x1+x2+x3 ~ y, data=resultb, type="l", pch=LETTERS[1:3], lty=c(1:3), main="For k=3, theata1=5") xyplot(x1+x2+x3 ~ y, data=resultc, type="l", pch=LETTERS[1:3], lty=c(1:3), main="For k=5, theata1=1") xyplot(x1+x2+x3 ~ y, data=resultd, type="l", pch=LETTERS[1:3], lty=c(1:3), main="For k=5, theata1=5") xyplot(x1+x2+x3 ~ y, data=resulte, type="l", pch=LETTERS[1:3], lty=c(1:3), mai...