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Sorry for messed up text. Here it goes again: I am learning to use the gsDesign package. I have a question about Pocock and OBF boundary. As far as I can understand, these 2 boundaries require equal spacing between interim analyses (maybe this is not correct?). But looks like I can still use gsDesign to run an analysis based on unequal spacing:? >

Hi, I am learning to use your gsDesign package!?I have a question about Pocock and OBF boundary. As far as Iunderstand, these 2 boundaries require equal spacing between interim analyses(maybe this is not correct?). But I can still use gsDesign to run an analysisbased on unequal spacing:?gsDesign(k=2,test.type=2,timing=c(0.75,1),alpha=0.05,sfu='Pocock')Symmetrictwo-sided group sequential

Still failed. The first secret is in your email program settings, to use Plain Text format (at least for emails you send to this mailing list). The second secret tool to use is the reprex package to let you verify that your code example will do on our computers what it is doing on your computer before you send it to us. That will also involve giving us some sample data or referencing some data

> On 23 Sep 2017, at 01:32, array chip via R-help <r-help at r-project.org> wrote: > > Hi, > > I am learning to use your gsDesign package! I have a question about Pocock and OBF boundary. As far as Iunderstand, these 2 boundaries require equal spacing between interim analyses(maybe this is not correct?). But I can still use gsDesign to run an analysisbased on unequal

How would I find the Percent of FuelTypeNum within the Band given AvailableMW? example: type 1 is 1% of PB0 type 2 is 54% of PB0 type 4 is 4% of PB0 type 5 is 42% of PB0 Note: the Bands and fuel types are not always constant. Data: FuelTypeNum Bands AvailableMW AvailableMWNewFormat 1 PB0 185319 185.319 2 PB0 18352000 18352 4 PB0 1338785 1338.785 5 PB0 14189756 14189.756 2 PB1

Hello!, i've just compared the 1.0.3 release with the master branch on a BeagleBone Black (AM335x 1GHz ARM Cortex-A8 with NEON floating-point accelerator) and Arch Linux ARM. At the moment I dont no why, but I see that 1.1 is much slower in encoding. Are there any default changes, that I missed and could explain this? Normaly I suggested a better performance with 1.1 and the ARM

Hello, I am trying to filter a data set like below so that the peaks in the Phase value are more obvious and can be identified by a peak finding function following the useful advise of Carl Witthoft. I have written the following for(i in length(data$Phase)){ newphase=if(abs(data$Phase[i+1]-data$Phase[i])>6){ data$Phase[i+1] }else{data$Phase[i] } } I get the following error which I have not

I don't understand which is the problem Could you help me please? Thanks in advance Marta > str(data_indiciN2) 'data.frame': 200 obs. of 36 variables: $ gruppo: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ... $ I001N2: num 19.32 8.22 28.35 7.24 14.7 ... $ I002N2: num 2.92 2.54 0.11 1.6 7.12 ... $ I003N2: num -22.362 -0.222 -19.291

Hi I have a set of data with both quantitative and categorical predictors. After scaling of response variable, i looked for multicollinearity (VIF values) among the predictors and removed the predictors who were hinding some of the other significant predictors. I'm curious to know whether the predictors (who are not significant) while doing simple 'lm' will be involved in

Hi All, Can someone help me?The way to do this may be very easy but i do not know. *Question1:----* factanal() function produces the results in this way:-- *RESULTS:--* *>fact1<- factanal(data_withNA,factors=1,rotation="none") >fact1$"loadings"* Loadings: Factor1 i1 0.784 i2 0.874 i3 0.786 i4 0.839 i5 0.778 i6 0.859 i7 0.850 i8 0.763 i9 0.810 i10 0.575

I have used the greedy.wilks to stepwise discriminant analysis, but it doesn't work with my dataset. I don't understand which is the problem Could you help me please? Thanks in advance Marta > str(data_indiciN2) 'data.frame': 200 obs. of 36 variables: $ gruppo: Factor w/ 2 levels "0","1": 2 2 2 2 2 2 2 2 2 2 ... $ I001N2: num 19.32 8.22 28.35 7.24

Hi, Just to clear things up... So 1.1 has some new analysis code that increases the amount of CPU. When building as floating point (which you appear to be doing, right?), the new code is enabled at complexity 7 and up (opusenc defaults to complexity 10 IIRC). This is why you've been seeing an increase in the CPU time. In version 1.0.x, complexity 5-10 are the exactly the same for music.

Hi I have a set of data with both quantitative and categorical predictors. After scaling of response variable, i looked for multicollinearity (VIF values) among the predictors and removed the predictors who were hinding some of the other significant predictors. I'm curious to know whether the predictors (who are not significant) while doing simple 'lm' will be involved in

Hi Everyone, I did a quick search of the list and it looks like this may not have been asked before... I'm trying to generate a matrix of random numbers between 0 and 1, with 6 columns, 10000 rows. About all I know is that runif(1) gives me the random number I'm looking for. Any help would be great! thanks, -Max

Hi Everyone, I did a quick search of the list and it looks like this may not have been asked before... I'm trying to generate a matrix of random numbers between 0 and 1, with 6 columns, 10000 rows. About all I know is that runif(1) gives me the random number I'm looking for. Any help would be great! thanks, -Max

Hello, Thank you to all those great folks that have helped me in the past (especially Dennis Murphy). I have a new challenge. I often generate time-series data sets that look like the one below, with a variable ("Phase") which has a series of flat-topped peaks (sample data below with 5 "peaks"). I would like to calculate the phase value for each peak. It would be great to

The time appears to be perfect inside dom0, however all the domU''s tend to have a slightly faster date which gets further out of sync every day. I''m currently using Xen 3.0.3 with Gentoo Linux, under 3.0.2 I had no problems with domU clocks. Are there any known issues which could cause this? I''d strongly prefer not to run ntpd in every domU, having all domU clocks in

I have a dataframe called "data" with 5 records (in rows) each of which has been scored on each of many variables (in columns). Five of the variables are named var1, var2, var3, var4, var5 using headers. The other variables are named using other conventions. I can create a new variable called var6 with the value 15 for each record with this code: > var6=var1+var2+var3+var4+var5

Hi, I am trying to make a multi-class classification tree by using rpart. I used MASS package'd data: fgl to test and it works well. However, when I used my small-sampled data as below, the program seems to take forever. I am not sure if it is due to slowness or there is something wrong with my codes or data manipulation. Please be advised ! The data is described as the output from str()

... and the mailing list is picky about attachments... whatever you attached did not conform to the stringent requirements mentioned in the Posting Guide. Pasting the code right into the email is usually safest, though you DO have to post using plain text (as the Posting Guide indicates) or your code may get mangled by the automatic html format removal. On May 15, 2018 7:04:31 AM PDT, Bert Gunter