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Hi Every one, I have a dataframe "class" with "name", "sex", "age", "height", "Weight". if i caluclate summary statistics with the below code numSummary(class[,c("Height", "Weight")], groups=class$Name, statistics=c("mean", "sd", "quantiles"), quantiles=c(0, .25,.5,.75,1)) iam getting output like this Variable: Height mean sd 0% 2...

Hi, is there any package/function that can tell if a numeric vector (continuous data) has a bimodal or trimodal distribution and caluclate the location of the corresponding modes? Thanks

Dear community, I have a little problem filling in a vector with loop output. I think the problem is the following: I am caluclating the index which indicates where the loop output should be placed at by a formula. But when I want to fill in or read out some specific index places this doesn't work properly. Let me show you my code: # CODE ################ ln_0 <- 0 ln_max <- 20 ln_schritt <- 0.1 l_frak_0 <-...

Dan Nordlund wrote: "It would be necessary to see the code for your 'brief test' before anyone could meaningfully comment on your results. But your results for a single test could have been a valid "random" result." I've re-created what I did below. The problem appears to be with the weighting process: the unweighted sample came out much closer to the actual

...osts, you could scale > document boosts at indexing time by some factor related to age and > that will factor into scoring. Boost won''t help me here, i''ve even set the boost value for relevance to 0.0, as it should not be part of the query.. Is there any way on how to recaluclate the score? Thanks, Ben -- Posted via http://www.ruby-forum.com/.

I tried to post this question two times, each time it seemed to fail, since " An embedded and charset-unspecified text was scrubbed..." So I try it again: I fitted a mixture density of two gaussians two my data. I now want to caluclate the standard errors of the estimates via the boot.se command of the mixtools package. My question is now, if the output is correct? It seems a bit odd to me, so is this correct what I am doing and can I rely on the values? My data can be found at: http://s000.tinyupload.com/?file_id=09285782882...

When I callculate a linear model, then I can compute via confint the confidencial intervals. the interval level can be chosen. as result, I get the parameter of the model according to the interval level. On the other hand, I can compute the prediction-values for my model as well with predict(object, type=c("response") etc.). Here I have also the possibility to chose a level for the

Dear UseRs, I'm running a chi-squared test where the expected matrix is the same as the observed, after rounding. R reports a X-squared of zero with a p value of one. I can justify this because any other result will deviate at least as much from the expected because what we observe is the expected, after rounding. But the formula for X-squared, sum (O-E)^2/E gives a positive value. What

...if you do > > price_beer = Price::new # using default of > Time::now here! > price_wine = Price::new ''valid_starting_at'' => ''now'' # but not here! > > # begin transaction > # insert price_beer > # caluclate the distance to the region producing your wine - takes 1 second > # insert price_wine > > now the price of beer and the price of wine will have different valid_starting > times even though both were inserted under a transaction with a time of ''now''! > > late...

line 212 of postgresql_adapter.rb is return Time.now.to_s if value =~ /^\(''now''::text\)::(date|timestamp)/ i don''t think this will work. in postgresql the field ''now'' is pinned to the SAME TIME for the duration of a transaction. eg. if you do begin transaction; insert into t values(42, ''now''); # sleep one minute