similar to: Refer to previous row

Here is my model with interaction terms and control variables (I changed variables names for easy read): reg1 <- lm(y ~ x1*x2*x3 +control1 + control2 + control3) x1 ranges from 0 to 6; x2 from 0 to 5; and x3 from 0 to 4. All three are discrete ordinal variables; but I will treat them as continuous variables. (a) How can I see the predicted values of y for each of these scenarios (210

Hi all, newbie question: I am trying to set up a very simple loop without succeeding. Let's say I have monthly observation of two variables for a year - Sales_2012_01, Sales_2012_02, Sales_2012_03, .... (total sales for jan 2012,feb 2012, etc.) - Customers_2012_01, Customers_2012_02, .... (total number of customers for jan 2012, etc.) and I want to create new monthly variables in

Dear R-helpers, I have a dataframe like this: ID X1 X2 X3 X4 X5 X6 49 1 1 1 0 NA NA 50 1 1 1 1 NA 1 I would like to convert a missing value (NA) that follows a 0 (zero) or another missing value (NA) into a 0 (zero). So, the above lines would be converted to: ID X1 X2 X3 X4 X5 X6 49 1 1 1 0 0 0 50 1 1 1 1 NA 1 I have been struggling with

Hello R users, I have two data sets like the following. Form of dataset: data: X1 X2 X3 X4 X5 1902 RE 3 594 9 1903 RE 3 1340 7 1904 AA 3 760 14 1908 RE 4 1759 18 1909 EX 2 387 1 2901 AU 6 3116

Hello I have data like this x1 x2 x3 x4 x5 I want to create a matrix similar to a correlation matrix, but with the difference between the two values, like this x1 x2 x3 x4 x5 x1 x2-x1 x3-x1 x4-x1 x5-x1 x2 x3-x2 x4-x2 x5-x2 x3 x4-x3 x5-x3 x4 x5-x4 x5 Then I

Below x1, x2 and x3 all have the same data and all have the same value for row.names(x); however, the internal values of their row.names differ. The internal value of row.names is c(NA, -4L) for x1, c(NA, 4L) for x2 and c("1", "2", "3", "4") for x3; nevertheless, identical regards x1 and x2 as identical while x3 is not identical to either of x1 or x2. Is

Hello, All, How can one sort on column and row names. For example: How can this X1 X3 X2 X1 1 0 0 X3 0 1 0 X2 0 0 1 become this? X1 X2 X3 X1 1 0 0 X2 0 1 0 X3 0 0 1 Thank you for your time! Jim [[alternative HTML version deleted]]

R users: Thanks in advance  How to generate missing at random (MAR)? assaedi76@yahoo.com Thanks [[alternative HTML version deleted]]

Hi, Using S=1000 and simdata <- replicate(S, generate(3000)) #If you want both "m1" and "m0" #here the missing values are 0 res1<-sapply(seq_len(ncol(simdata.psm1)),function(i) {x1<-merge(simdata.psm0[,i],simdata.psm1[,i],all=TRUE); x1[is.na(x1)]<-0; x1}) res1[,997:1000] #????? [,1]???????? [,2]???????? [,3]???????? [,4]??????? #x1??? Numeric,3000 Numeric,3000

Hi. This is likely a trivial problem but have not found a solution. Imagine the following dataframe: Lat Lon x1 x2 x3 01 10 NA NA .1 01 11 NA .2 .3 01 12 .4 .5 .6 I want to generate another column that consist of the first value in each row from columns x1 to x3. That is NewColumn .1 .2 .4 Any input greatly appreciated, Thanks, Camilo Camilo Mora, Ph.D.

Hi there, I just don't find the solution on the following problem. :( Suppose I have a dataframe with two predictor variables (x1,x2) and one depend binary variable (y). How is it possible to define a glm object (family="binomial") with a user defined logistic function like p(y) = exp(a + c1*x1 + c2*x2) where c1,c2 are the coefficents which I define. So I would like to do no

Hi I have a data-frame which look like this X1 X2 X3 1 3 5 2 4 6 3 6 1 I want to apply a formula Y=6*X1 + 7*X2 + 8*X3 for every row Thanks in Advance -- View this message in context: http://r.789695.n4.nabble.com/how-to-call-a-function-for-each-row-tp4122906p4122906.html Sent from the R help mailing list archive at Nabble.com.

Hello, I found a potential problem in R 2.1.0 (and R 2.0.1) I expect that > tmp <- FUN(x1, x2, x3, x4) > as.data.frame(tmp) is the same as > as.data.frame(FUN(x1, x2, x3, x4)) since the tmp variable in this case is unnecessary. However, below I will demonstrate that under an odd set of conditions, I can correctly perform as.data.frame(tmp), but not as.data.frame(FUN(x1, x2, x3,

Hi, I have a data frame that looks like this: >x x1 x2 x3 A 1 1.5 B 2 0.9 B 3 2.7 C 7 1.8 D 7 1.3 I want to "group" by the x1 column and in the case of multiple x$x1 values (e.g., "B")d, return rows that have the smallest values of x2. In the case of rows with only one value of x1 (e.g., "A"), return the row as is. How can I do that?

Hi, Here i have a matrix like this, OLDMatrix <- X1 X2 X3 ----- ------ ------ 22 24 23 25 27 27 10 13 15 the thing is, im running two function(SUM,COUNT) to get output in another matrix called NEWMatrix NEWMatrix <- c("SUM",colSums(OLDMatrix )) NEWMatrix <- c("COUNT",colSums(!is.na(OLDMatrix

hello I make a subroutine that give-me a (mathematical) function in string format. I would like transform this string into function ( R function ). thanks for any tips. cleber #e.g. fun_String = "-100*x1 + 0*x2 + 100*x3" fun <- function(x1,x2,x3){ return( ############ evaluation( fun_String ) ############ ) True String mathematical function :-( :-( > nomes [1]

Hi R-helpers! I have the following dataframe: firm<-c(rep(1:3,4)) year<-c(rep(2001:2003,4)) X1<-rep(c(10,NA),6) X2<-rep(c(5,NA,2),4) data<-data.frame(firm, year,X1,X2) data So I want to obtain the same dataframe with a variable X3 that is: X1, if X2=NA X2, if X1=NA X1+X2 if X1 and X2 are not NA So my final data is X3<-c(15,NA,12,5,10,2,15,NA,12,5,10,2)

Dear R-help, Let's say `x1' and `x2' are very long vectors (length=5e5, say) with same set of names but in different order. If I want to sort `x2' in the order of `x1', I would do x2[names(x1)] but the amount of time that takes is quite prohibitive! Does anyone have any suggestion on a more efficient way to do this? If the two vectors are exactly the same length (as I

hi folks, I'm trying to build a table that contains information about a series of General Linear Models in order to calculate Akaike weights and other measures to compare all models in the series. i have an issue with indexing models and extracting the information (loglikehood, AIC's, etc.) that I need to compile them into the table. Below is some sample code that illustrates my

Hi, I recently ran into an inconsistency in the way model.matrix.default handles factor encoding for higher level interactions with categorical variables when the full hierarchy of effects is not present. Depending on which lower level interactions are specified, the factor encoding changes for a higher level interaction. Consider the following minimal reproducible example: -------------- >