similar to: Generating a best fit line for non linear data

Hi everyone, I'm involved in a discussion with a colleague. He suggested a sample design for a finite-sized process that (to all intents and purposes) involves tossing a coin and examining the unit if the coin shows Heads. I should emphasize that we're both approaching the problem from a design-based sampling theory point of view. So I have no argument about the appropriateness of the

This is part of my program. I am getting an error, that I cannot figure out, any help would very much appreciated, thanks. # subset variables arc <- arc[,c("SNAP", "code", "ncode", "var", "n_total")] Error in `[.data.frame`(arc, , c("SNAP", "code", "ncode", : undefined columns selected arc$N_eff <-

Dear all, I am facing the following problem in optimization: w = (d, o1, ..., op, m1, ..., mq) is a 1 + p + q vector I want to determine: w = argmin (a - d(w))' A (a - d(w)) where a is a 1xK marix, A is the covariance matrix of vector a, d(w) is a 1xK vector which parameters are functions of parameters d, o1 .. op, m1 .. mq. Is there some function to solve this problem easily? I know

The R "cut" command is entirely different from the UNIX "cut" command. The latter retains selected fields in a line of text. I can do that kind of manipulation using sub() or gsub(), but it is tedious. I assume there is an R function that will do this, but I don't know its name. Can you tell me? I'm also guessing that there is a web page somewhere that will tell

Hi, How i can install the package "adapt" in some version of R for mac? i try in 2.13, 2.9,2.7 and other previous versions... and nothing happens. and another question: There are some packages that do the same but that it is implemented for mac? (calculate integrals in 2 or more dimmensions). help me please, it's for an important work. greetings. -- Matías Hernán Ramírez

Hello. I'm trying to use the functions pandit and treebase. They are in the package apTreeshape. Once I've loaded the package, R responses: - no function pandit/treebase. Somebody knows why or what is the reason? Thanks, Arnau. ------------------------------------------------------------ Arnau Mir Torres Edifici A. Turmeda Campus UIB Ctra. Valldemossa, km. 7,5 07122 Palma de Mca.

I am wondering how to obtain the model/equation at each level automatically in a regression model with a few factors without looking at summary of the lm model. For example, consider lm.factors <- lm(y ~ x1 + factor(x2)*factor(x3)+x4*factor(x5)) The coefficients of lm.factors in summary(lm.factors) might be complicated. I would like to have the equation at each level from lm.factor. Could you

Hi, I have three matrices (X,Y,P) with the same dimension. The X,Y grid is regular and I want to perform linear interpolation to pick out certain points. In matlab appropriate call is something like Pout=interp2(X,Y,P,Xout,Yout, method="linear") where Xout and Yout are the locations where I want the Pout data (typically a different grid). (Scipy has this routine in

I'm fitting a regression model for censored data with three categorical predictors, say A, B, C. My final model based on the survreg function is Surv(..) ~ A*(B+C). I know the three-way group mean estimates can be computed using the predict function. But is there any way to obtain two-way group mean estimates, say estimated group mean for (A1, B1)-group? The sample group means don't

Dear community, I uploaded an excel with read.xls. My xls file actually have a column which is an id, ("plot" is the id) : plot height area 34 7.6 5.4 85 3.2 4.1 89 5.4 8.4 121 6.7 6.2 ... 1325 2.1 1.5 However R uses another id, this way: r id plot height area 1 34 7.6 5.4 2 85 3.2 4.1 3 89 5.4 8.4 4 121

I have a vector with lots of different numbers. I need to make a graph showing the Uniform Distribution of the figures. I have created a graph showing all the different values, but now want individual Gaussian Kernel round each point. This is what I have but each time it comes up with an error as I have just based it on the Normal Distribution, but I'm not sure what I need to change to make it

I'm trying to find the variance of various outputs in a matrix: for(l in 2:vl){ for(o in 1:(l-1)){ # Make sure the inputs are for the matrix "m" input3=rownames(v)[o] input4=colnames(v)[l] r=t[(t$Rec1==input3 & t$Rec2==input4),output] if(length(r)==0){ r=t[(t$Rec1==input4 & t$Rec2==input3),output] } v[l,o]=var(q,na.rm=TRUE)

Hi, Can someone please offer me some guidance? I imported some data. One of the columns called "JOBTITLE" when imported was imported as a factor column with 416 levels. I subset the data in such a way that only 4 levels have data in "JOBTITLE" and tried running randomForest but it complained about "JOBTITLE" having more than 32 categories. I know that is the limit

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Hi, I am attempting to fit a ARMA/GARCH regression model without success. ### ARIMA-GARCH model with regressor ### ### Time series data: A multivariate data set. cov.ts.dq = cov.ts[1:4,"dq1"][!is.na(cov.ts[,"dq1"])] cov.ts.day = ts.intersect(dq = diff(q.ts), day = lag(q.ts, -1)) ### The following R scripts work: (summary(no.day.fitr <- garchFit(dq ~ arma(0,3) +

Hi everybody I couldn't find the solution to what must be quite a simple problem. Maybe you can help? treatment session period stage wage_accepted market 1 1 1 1 1 25 public 2 1 1 1 1 19 privat 3 1 1 1 1 15 public 4 1

Hi, Is it possible (i am sure it is) to subset data from a data.frame on the basis of SQL >LIKE< operator. I.e., i would like to subset a data where only values which contains a string >GP< would be used? Example: Gp<-subset(DF, DF$USCS like >GP<) This like of course is not working, Thanks, m [[alternative HTML version deleted]]

Hi, I have a erdos-renyi game with 6000 nodes and probability 0.003. g1 = erdos.renyi.game(6000, 0.003) How to create a Watts Strogatz game with the same probability. g1 = watts.strogatz.game(1, 6000, ?, ?) What should be the third and fourth parameter to this argument. -- View this message in context: http://r.789695.n4.nabble.com/Watts-Strogatz-game-tp3491922p3491922.html Sent from the R

I am attempting to use package boot to summarize and compare the performance of three models. I'm using R 2.13.0 in a Win32 environment. My statistic function returns a vector of 6 values, 3 of which are error rates for different models, and 3 are pairwise differences between those error rates. It looks like: multiEst<-function(dat,i) { .... c(E1,E2,E3,E2-E1,E3-E1,E3-E2); }

Dear R users: Recently, I learn to use penalized logistic regression. Two packages (penalized and glmnet) have the function of lasso. So I write these code. However, I got different results of coef. Can someone kindly explain. # lasso using penalized library(penalized) pena.fit2<-penalized(HRLNM,penalized=~CN+NoSus,lambda1=1,model="logistic",standardize=TRUE) pena.fit2