search for: nmean

...n tapply. I would like to plot with different colours according to the Year and show the "Species" as data labels. My data looks like this: Species d13C d13N Year "Species1" 14,4 11.5 2009 "Species2" ... ... .... >Nmean<-tapply(d15N,list(Year,Species),mean) >Cmean<-tapply(d13C,list(Year,Species),mean) ##works fine, returns something like this Species1 Species2 Species3 2009 20.3 13.4 13,5 2011 NA 23.5 14.5 20...

...um of r statistics each distributed as the Studentized range of means calculated from c random samples of size n from normal populations. The rc samples are assumed to be mutually independent and a common pooled?within?samplevariance is used throughout." So the connection is nranges == r, and nmeans == c. (n never actually factors in because sqrt(n) is part of the standardization) For the typical application, r is 1 for the usual studentized range distribution. E.g. for two large groups: > qtukey(.95,2,df=Inf) [1] 2.771808 As there is only one difference to consider, this should be dist...

Dear all, I wanted to compare Bonferroni vs TukeyHSD correction over a range of groups and group sizes, and wanted to use the function qtukey. In the help documentation it says qtukey(p, nmeans, df, nranges = 1, lower.tail = TRUE, log.p = FALSE) Arguments q vector of quantiles. p vector of probabilities. nmeans sample size for range (same for each group). df degrees of freedom for s (see below). nranges number of groups whose maximum range is considered. log.p logical; if TRUE...

Dear all, I'm using R to perform multiple comparison testing on agriculture genotype trials. To perform the Duncan's MRT, I use the qtukey() function with the following syntax: qtukey(p = ((1 - 0.05) ^ (pos - 1)), nmeans = pos, df = ni) I experience a strange behaviour when the number of means in the trial and the number of residual degrees of freedom (ni) becomes high (orientatively pos > 30 and ni > 60), i.e. the function returns NaN together with the following message: convergence failed in 'qtuk...

...017 11:36:47 AM PDT, Ursula Garczarek <Ursula.Garczarek at cytel.com> wrote: >Dear all, >I wanted to compare Bonferroni vs TukeyHSD correction over a range of >groups and group sizes, and wanted to use the function qtukey. > >In the help documentation it says > >qtukey(p, nmeans, df, nranges = 1, lower.tail = TRUE, log.p = FALSE) >Arguments >q > >vector of quantiles. > >p > >vector of probabilities. > >nmeans > >sample size for range (same for each group). > >df > >degrees of freedom for s (see below). > >nranges >...

...x, col="red", lwd=3) kurtosis_val <-(sum((x-mean(x))^4 ))/(var(x)*var(x))/length(x)-3 skewness<-function(x) { m_skew=mean(x) me_skew=median(x) s_skew=sqrt(var(x)) sk_skew=(m_skew-me_skew)/s_skew return(sk_skew) } title_text<-c("Title Text", "\nMean = ", format(mean(x), digits=4, scientific=F), " Standard Deviation = ", format(sd(x), digits=4, scientific=F),"\n Skewness = ", format(skewness(x), digits=4, scientific=F), "Kurtosis =", format(kurtosis_val, digits=4, scientific=F)) mtext(title_text, NORTH<-3,...

...# And compare r/e2 (SS = 69.500 with 2 GL) like this: # r1 vs (r2,r3 ) / e2 # r2 vs r3 / r1 / e2 # # ------------------------------End the problem---------------------------- mds = model.tables(av1, ty = 'means') detach(df) cat('\nData:'); cat('\n') print(df) cat('\nMeans:'); cat('\n') print(mds) cat('\nANOVA:'); cat('\n') print(summary(av1)); cat('\n') cat('\nANOVA - E effect in R levels:'); cat('\n') print(efR_E); cat('\n') cat('\nANOVA - R effect in E levels:'); cat('\n') print(efE_R)...

...esn't work and reports NULL res2$df.residual doesn't work and reports NULL Is this an undocumented feature or an error? It sure plays havoc with Dr. Bates' contribution of Tukey.aov which works with res0 and res1 but doesn't work with res2 and reports Error in qtukey(p, nranges, nmeans, df, lower.tail, log.p) : Non-numeric argument to mathematical function A simple but inelegant workaround is to input mse and df.residual as function arguments in addition to the aov object. Does anyone have a better solution? Thank you, Peter B. -- Peter B. Mandeville...

I am embarrassed to have to ask this but can anyone tell me of a Tukey multiple comparisons procedure available for R? I have looked through the search page, through the FAQ, and in the index of V&R (1999), and I still can't find such a thing. I see there is a ptukey function and a qtukey function but that is as far as I got. Do I need to roll my own? -- Douglas Bates

...2/r2' = 2, 'e1 vs e2/r3' = 3))) av3 = aov(y ~ e/r) efE_R = summary(av3, split = list('e:r' = list('r/e1' = c(1,3), 'r/e2' = c(2,4)))) mds = model.tables(av1, ty = 'means') detach(df) cat('\nData:'); cat('\n') print(df) cat('\nMeans:'); cat('\n') print(mds) cat('\nANOVA:'); cat('\n') print(summary(av1)); cat('\n') cat('\nANOVA - E effect in R levels:'); cat('\n') print(efR_E); cat('\n') cat('\nANOVA - R effect in E levels:'); cat('\n') print(efE_R)...

...2/r2' = 2, 'e1 vs e2/r3' = 3))) av3 = aov(y ~ e/r) efE_R = summary(av3, split = list('e:r' = list('r/e1' = c(1,3), 'r/e2' = c(2,4)))) mds = model.tables(av1, ty = 'means') detach(df) cat('\nData:'); cat('\n') print(df) cat('\nMeans:'); cat('\n') print(mds) cat('\nANOVA:'); cat('\n') print(summary(av1)); cat('\n') cat('\nANOVA - E effect in R levels:'); cat('\n') print(efR_E); cat('\n') cat('\nANOVA - R effect in E levels:'); cat('\n') print(efE_R)...

Hi, What is expression IC on TukeyHSD? contrast +/- qtukey(.95, nmeans, df) * sqrt(MSe/n) ? Thanks, Bruno [[alternative HTML version deleted]]

...= aov(y ~ e/r) efE_R = summary(av3, split = list('e:r' = list( 'r/e1' = c(1,3), 'r/e2' = c(2,4)))) mds = model.tables(av1, ty = 'means') detach(df) cat('\nData:'); cat('\n') print(df) cat('\nMeans:'); cat('\n') print(mds) cat('\nANOVA:'); cat('\n') print(summary(av1)); cat('\n') cat('\nANOVA - E effect in R levels:'); cat('\n') print(efR_E); cat('\n') cat('\nANOVA - R effect in E levels:'); cat('\n&...

Hello R-users, I've been looking for a function performing one and two sample Hotelling test for testing equality of mean vectors. Has anyone implemented such a function in R? thanks a lot, Bill ============== Bill Donner Statistician