similar to: Change dataframe-structure

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Is it possible in R to subset a dataframe by more than one factor, all at once? For instance, I have the dataframe: >data p1 p2 p3 p4 p5 p6 p7 p8 p9 p10 pred 1 0 1 0 0 0 0 0 0 0 0 0.5862069 4 0 0 0 0 0 0 0 0 0 1 0.5862069 5 0 0 0 0 0 0 1 0 0 0 0.5862069 6 0 0 0 0 0 0 0 1 0 0 0.5862069 7 0 0 1 0 0 0 0 0 0

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Dear list, I have 9 repeated measures (measurement variable == 'Delta13C') for individuals (ID variable == 'Individual_ID'. Each repeated measure is "indexed" (right term?) by the variable 'FeatherPosition' and given as c('P1', 'P2', 'P3', 'P4', 'P5', 'P6', 'P7', 'P8', 'P9'). I would like to

Hi to all the people again, I was writting a simply function in R, and wish to collect the results in a excel file. The work goes as follows, Ciervos<-function(K1, K0, A, R,M,Pi,Hembras) {B<-(K1-K0)/A T1<-(R*Pi*Hembras-M*Pi+B)/(Pi-M*Pi+R*Pi*Hembras) P1<-Pi-B R1<-P1*Hembras*R M1<-P1*M T2<-(R1-M1+B)/(P1-M1+R1) P2<-P1-B R2<-P2*Hembras*R M2<-P2*M

Dear all, Can any one tell me how can i perform Orthogonal Polynomial Regression parameter estimation in R? -------------------------------------------- Here is an "Orthogonal Polynomial" Regression problem collected from Draper, Smith(1981), page 269. Note that only value of alpha0 (intercept term) and signs of each estimate match with the result obtained from coef(orth.fit). What

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Dear R experts, I am trying to solve this problem, related to the possibility of changing the shape of a data frame using a "pivoting-like" function. I have a dataframe df of observations as follows: ID VALIDITY YEAR PROPERTY PROPERTY VALUE A1 2007 P1 V1 A1 2007 P2 V2 A1 2007 P3 V3 A1 2008 P1 V10 A1 2008 P2 V20 A2 2007 P5 V50 A2 2008 P6 V20 A3 2007

I'm trying to use odesolve for integrating various series of coupled 1st order differential equations (derived from a system of enzymatic catalysis and copied below, apologies for the excessively long set of parameters). The thing that confuses me is that, whilst I can run the function rk4: out <- rk4(y=y,times=times,func=func, parms=parms) and the results look not unreasonable:

I am having some problems using Quadprog in R. I want to minimize the objective function : 200*P1-1/2*10*P1^2+100*P2-1/2*5*P2^2+160*P3-1/2*8*P3^2+50*P4-1/2*10*P4^2+50*P 5-1/2*20*P5^2+50*P6-1/2*10*P6^2, Subject to a set of constrains including not only the variables P1, P2, P3, P4, P5, P6, but also the variables X1, X2,X3,X4,X5,X6,X7,X8,X9. As the set of variables X's are not

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Hi everyone, I have a question for R code to merge. Say I have two dataframes: File1 is: V1 V2 V3 V4 1 100 101 name1 2 200 201 name2 2 300 301 name3 3 400 401 name4 3 500 501 name5 4 600 601 name6 4 700 701 name7 File2 is: V1 V2 V3 V4 1 50 55 p1 3 402 449 p2 4 550 650 p3 4 651 660

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Dear list, I have a dataset where we sampled multiple individuals either 1 or 9 times. Our measurement variable is 'Delta13C' (see below sample dataset). I cannot figure out how to efficiently use a vector command (preferably) or a loop to create a new vector of the names of the individuals sampled 9 times. Note that the 'FeatherPosition' variable will only be "P1" for

On Tue, Dec 10, 2013 at 11:58 AM, Hans Wennborg <hans at chromium.org> wrote: > It would be nice if we could make the TypePrinter not print the > calling convention if it's the default one for the ABI, but > TypePrinter doesn't have a lot of context.. no Sema, no ASTContext :/ > Does this patch fix any failures for you? It doesn't fix that test case, unfortunately.

I think we need to relax the test cases. MSVC usually prints the calling convention, and it's often useful information. Maybe we can make the diagnostic text smaller by using the __thiscall, __cdecl, __stdcall, etc keywords when printing types with LangOpts.MicrosoftExt, but it will require moving the attribute from after the identifier to before, which is exciting. On Tue, Dec 10, 2013 at

Hello everybody! I have the following problem: I'd like to select a sample from a subsample in a dataset. Actually, I don't want to select it, but to create a new variable sampleNo that indicates to which sample (one or two) a case belongs to. Lets suppose I have a dataset containing 40 cases: data <- data.frame(var1=seq(1:40), var2=seq(40,1)) The first sample (n=10) I drew like

Hi everyone, I'm observing what I believe is weird behaviour when attempting to do something very simple. I want a correlation matrix, but my matrix seems to contain correlation values that are not found when executed on pairs: > test2$P2 [1] 2 2 4 4 1 3 2 4 3 3 2 3 4 1 2 2 4 3 4 1 2 3 2 1 3 > test2$HP_tot [1] 10 10 10 10 10 10 10 10 136 136 136 136 136 136 136 136 136

I would like to fit the following function on my data. out.nls<-nls(z ~ p1+ (p2*dat)+(p3*dat^2)+(p4*dat^3)+(p5*AgeS)+(p6*AgeS^2)+(p7*AgeS^3)+ (p8*(dat*AgeS))+(p9*(dat^2*AgeS))+(p10*(dat^3*AgeS))+ (p11*(dat*AgeS^2))+(p12*(dat*AgeS^3))+(p13*(dat^2*AgeS^2))+ (p14*(dat^2*AgeS^3))+(p15*(dat^3*AgeS^3)),

Hola todos Cuando realizo las predicciones del modelo multinomial con el paquete nnet, estas cambian cada vez que lo ejecuto ... saben por qué pasa esto ?? Gracias por la ayuda. [[alternative HTML version deleted]]