search for: 6.400000

Dear all, I have a matrix with positive and negative values. >From this I would like to produce 2 matrices: 1st - retaining positives and putting NA in other positions 2nd - retaining negatives and putting NA in other positions and then apply rowMeans for both. I am trying to use the function ifelse in the exemplified form: ifelse(A>0,A,NA) but by putting A as a 2nd parameter it

maybe it's in the data? So here it comes. > sv.growth Grouped Data: length ~ meas | box_id meas spec comp water box_id sprouts leaves length long.sprout 1 1 Sv control moist 1 8.800000 37.80 211.2000 60.6 2 1 Sv xfull moist 2 7.000000 8.00 174.8000 62.8 3 1 Sv control moist 3 9.000000

Dear R users I have a really simple question (hoping for a really simple answer :-): Having estimated the spectral density of a time series "x" (heart rate data) with: x.pgram <- spectrum(x,method="pgram") I would like to compute the power in a specific energy band. Assuming that frequency(x)=4 (Hz), and that I am interested in the band between f1 and f2, is the

Hi, Our in-house AS400 based application produce a timer file as follows: TranName,Date Time, TimeA,A+B, TimeB MAC00029,20061027 112500.030,703,703,0 MAC00029,20061027 112500.342,703,719,16 MAC00056,20061027 112500.920,484,500,16 MAC00029,20061027 112501.186,812,812,0 MAC00029,20061027 112502.092,672,672,0 MAC00029,20061027 112502.264,687,687,0 MAC00056,20061027 112503.264,453,453,0

Dear all, I am new to R and to it's programming philosophy. The following function is supposed to work on a vector, but I can't figure out how to do that without looping through every element of it. Is there a more elegant way? Note: I have shortened it, so it is NOT correct from the pipe hydraulics point of view # Calculate wall friction factor # reynolds: Reynolds number # dk:

Fellow R Users: I'm not extremely familiar with lda or R programming, but a recent editorial review of a manuscript submission has prompted a crash cousre. I am on this forum hoping I could solicit some much needed advice for deriving a classification equation. I have used three basic measurements in lda to predict two groups: male and female. I have a working model, low Wilk's lambda,

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