Hi, I have a problem with Kolmogorov-Smirnov test fit. I try fit distribution to my data. Actualy I create two test: - # First Kolmogorov-Smirnov Tests fit - # Second Kolmogorov-Smirnov Tests fit see below. This two test return difrent result and i don't know which is properly. Which result is properly? The first test return lower D = 0.0234 and lower p-value = 0.00304. The lower 'D' indicate that distribution function (empirical and teoretical) coincide but low p-value indicate that i can reject hypotezis H0. For another side this p-value is most higer than p-value from second test (2.2e-16). Which result, test is most propertly?
matr = rbind(c(1,2)) layout(matr) # length vectorSentence = 11999 vectorSentence <- c(....) vectorLength <- length(vectorSentence) # assume that we have a table(vectorSentence) # 1 2 3 4 5 6 7 8 9 # 512 1878 2400 2572 1875 1206 721 520 315 # Poisson parameter param <- fitdistr(vectorSentence, "poisson") # Expected density density.exp <- dpois(1:9, lambda=param[[1]][1]) # Expected frequ. frequ.exp <- dpois(1:9, lambda=param[[1]][1])*vectorLength # Construct numeric vector of data values (y = vFrequ for Kolmogorov-Smirnov Tests) vFrequ <- c() for(i in 1:length(frequ.exp)) { vFrequ <- append(vFrequ, rep(i, times=frequ.exp[i])) } # Check transformation plot(density.exp, ylim=c(0,0.20)) == plot(table(vFrequ)/vectorLength, ylim=c(0,0.20)) plot(table(vectorSentence)/vectorLength) plot(density.exp, ylim=c(0,0.20)) par(new=TRUE) plot(table(vFrequ)/vectorLength, ylim=c(0,0.20)) # First Kolmogorov-Smirnov Tests fit ks.test(vectorSentence, vFrequ) # Second Kolmogorov-Smirnov Tests fit ks.test(vectorSentence, "dpois", lambda=param[[1]][1]) # First Kolmogorov-Smirnov Tests fit return data Two-sample Kolmogorov-Smirnov test data: vectorSentence and vFrequ D = 0.0234, p-value = 0.00304 alternative hypothesis: two-sided Warning message: In ks.test(vectorSentence, vFrequ) : cannot compute correct p-values with ties # Second Kolmogorov-Smirnov Tests fit return data One-sample Kolmogorov-Smirnov test data: vectorSentence D = 0.9832, p-value < 2.2e-16 alternative hypothesis: two-sided Warning message: In ks.test(vectorSentence, "dpois", lambda = param[[1]][1]) : cannot compute correct p-values with ties Best Marcin M. -- View this message in context: http://r.789695.n4.nabble.com/Kolmogorov-Smirnov-test-tp3479506p3479506.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.