search for: xij

...g by defining a [<- class; the question that I still > don't see answered in documentation or source code is, why/where is [<- > called, exactly? > Your rbind(DF, DF) call dispatches to base::rbind.data.frame(). The `[<-` call is this line: value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij That's where the storage.mode changes from integer to double. debug: value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij Browse[2]> debug: xij Browse[2]> storage.mode(xij) [1] "integer" Browse[2]> value[[jj]][ri] [1] "2019-05-26&...

...> > don't see answered in documentation or source code is, why/where is [<- > > > called, exactly? > > > > > Your rbind(DF, DF) call dispatches to base::rbind.data.frame(). The > > `[<-` call is this line: > > value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij > > > > That's where the storage.mode changes from integer to double. > > > > debug: value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij > > Browse[2]> > > debug: xij > > Browse[2]> storage.mode(xij) > &g...

...facCol[j] <- TRUE } else facCol[j] <- is.factor(xj) ordCol[j] <- is.ordered(xj) has.dim[j] <- length(dim(xj)) == 2 } } else for (j in 1:nvar) { xij <- xi[[j]] if (is.null(pi) || is.na(jj <- pi[[j]])) jj <- j if (facCol[jj]) { if (length(lij <- levels(xij)) > 0) { all.levs[[jj]] <- unique(c(all.levs[[jj]], lij))...

...ation or source code is, why/where is [<- > >> > > called, exactly? > >> > > > >> > Your rbind(DF, DF) call dispatches to base::rbind.data.frame(). The > >> > `[<-` call is this line: > >> > value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij > >> > > >> > That's where the storage.mode changes from integer to double. > >> > > >> > debug: value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij > >> > Browse[2]> > >> > debug:...

...facCol[j] <- TRUE } else facCol[j] <- is.factor(xj) ordCol[j] <- is.ordered(xj) has.dim[j] <- length(dim(xj)) == 2 } } else for (j in 1:nvar) { xij <- xi[[j]] if (is.null(pi) || is.na(jj <- pi[[j]])) jj <- j if (facCol[jj]) { if (length(lij <- levels(xij)) > 0) { all.levs[[jj]] <- unique(c(all.levs[[jj]], lij))...

...the question that I still > > don't see answered in documentation or source code is, why/where is [<- > > called, exactly? > > > Your rbind(DF, DF) call dispatches to base::rbind.data.frame(). The > `[<-` call is this line: > value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij > > That's where the storage.mode changes from integer to double. > > debug: value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij > Browse[2]> > debug: xij > Browse[2]> storage.mode(xij) > [1] "integer" > Browse[2...

..."3", "4", : duplicate 'row.names' are not allowed In addition: Warning message: non-unique values when setting 'row.names': ?1?, ?10?, ?2?, ?3?, ?4?, ?5?, ?6?, ?7?, ?8?, ?9? -- Looking at the code of rbind.data.frame, the error comes from the lines: -- xij <- xi[[j]] if (has.dim[jj]) { value[[jj]][ri, ] <- xij rownames(value[[jj]])[ri] <- rownames(xij) # <-- problem is here } -- if the rownames() line is dropped, all works well. What this line tries to do is to join the rownames of internal elements of the data.frames I...

...see answered in documentation or source code is, why/where is [<- >> > > called, exactly? >> > > >> > Your rbind(DF, DF) call dispatches to base::rbind.data.frame(). The >> > `[<-` call is this line: >> > value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij >> > >> > That's where the storage.mode changes from integer to double. >> > >> > debug: value[[jj]][ri] <- if (is.factor(xij)) as.vector(xij) else xij >> > Browse[2]> >> > debug: xij >> > Browse[2]&g...

...trying to caculate the MLEs for parameters of Inverse Gaussian distribution (in a k-sample problem with common mean) by using EM-Algorithm. I found some package for EM-Algorithm that are useful for missing or incomplete data and are not helpful for solving my problem. (Exactly, the problem is: Let Xij, i=1,..,k , j=1,...,ni, be a random sample from IG(?,?i). So the log-likelihood function is: log(L)=?(ni/2)*log(?i)-?? (?i/2*(?^2)*xij)*((xij-?)^2)+const. Find the MLEs for (?,?1,...,?k) by EM-Algorithm?) Could you please help me with that? I would like to thank you in advance for your help. best...

...ep(-1,4), rep(1,4) ) x2=c( rep(c(-1,-1,1,1),2) ) x3=c( rep(c(-1,1),4) ) x1*x2 x1*x3 x2*x3 ======================== suppose i have x1,x2,x3 i want to compute their ' two factor interactions', x1x2,x1x3 and x2x3, I wrote ======================== for(i in 1:2){ for( j in i+1:3){ xij=c() xij=xi*xj } } ======================== it did not seem to recognize xi and xj is there any suggestion? it would be wonderful if there exists a single command that i can use My ultimate aim is to find the 55 xixj s of the following data: http://n4.nabble.com/file/n1692945/test_pic.jpg test_p...

Debugging this issue: https://github.com/Rdatatable/data.table/issues/2008 We have custom class 'IDate' which inherits from 'Date' (it just forces integer storage for efficiency, hence, I). The concatenation done by rbind, however, breaks this and returns a double: library(data.table) DF = data.frame(date = as.IDate(Sys.Date())) storage.mode(rbind(DF, DF)$date) # [1]

The compositional data xi=(x_i1,x_i2,...,x_in), for each fixed i , xij>0, and sum(xij)=1; I want to compare the mean( u_i) of several groups i.e. H0: u_1=u_2=...=u_N or H0: u_11=u_21=...=u_N1 Are there any ANOVA tpye tools to do this work in R? Thanks, WEN S Q [[alternative HTML version deleted]]

...*sum(R[1:i])) GGamma[Idebut:Ifin,Idebut:Ifin]=PGamma } #Calcul de Sigma # Calcul de Vn X1=CentrageV(X,Xbar,n) Vn=t(X1)%*%X1/n ## Construction de Sigma GSigma=matrix(0,p*sum(R),p*sum(R)) for (i in 1:q ){ for (j in 1:R[i] ){ for (k in 1:q ){ for (l in 1:R[k]){ Xij=CentrageV(X,Xjhbar[[i]][j,],n) Xkl=CentrageV(X,Xjhbar[[k]][l,],n) Vijkl=t(W[[i]][j]*Xij)%*%(W[[k]][l]*Xkl)/n Vij=t(W[[i]][j]*Xij)%*%Xij/n11[[i]][j] Vkl=t(W[[k]][l]*Xkl)%*%Xkl/n11[[k]][l] if (i==1) Idebut=((j-1)*p)+1 else Idebut=((sum(R[1:(...

...-1)]))+1) 115 Ifin=(p*sum(R[1:i])) 116 GGamma [Idebut:Ifin,Idebut:Ifin]=PGamma 117 } 118 #Sigma calculation 119 # Calculation of Vn 120 X1=CenteringV(X,Xbar,n) 121 Vn=t(X1)%*%X1/n 122 ## Construction of Sigma 123 GSigma=matrix(0,p*sum(R),p*sum(R)) 124 for (i in 1:q ){ 125 for (j in 1:R[i] ){ 126 Xij=CenteringV(X,Xjhbar[[i]][j,],n) 127 Vij=t(W[[i]][,j]*Xij)%*%Xij/n11[[i]][j] 128 for (k in 1:q ){ 129 for (l in 1:R[k]){ 130 Xkl=CenteringV(X,Xjhbar[[k]][l,],n) 131 Vijkl=t(W[[i]][,j]*Xij)%*%(W[[k]][,l]*Xkl)/n 132 Vkl=t(W[[k]][,l]*Xkl)%*%Xkl/n11[[k]][l] 133 if (i==1) Idebut=((j-1)*p)+1 else Idebu...

I suspect there may be a bug in base::rbind.data.frame Below there is minimal example of the problem: m <- matrix (1:12, 3) dfm <- data.frame (c = 1 : 3, m = I (m)) str (dfm) m.names <- m rownames (m.names) <- letters [1:3] dfm.names <- data.frame (c = 1 : 3, m = I (m.names)) str (dfm.names) rbind (m, m.names) rbind (m.names, m) rbind (dfm, dfm.names) #not working rbind

...:Ifin]=PGamma > 117 } > > 118 #Sigma calculation > > 119 # Calculation of Vn > 120 X1=CenteringV(X,Xbar,n) > 121 Vn=t(X1)%*%X1/n > > 122 ## Construction of Sigma > 123 GSigma=matrix(0,p*sum(R),p*sum(R)) > 124 for (i in 1:q ){ > 125 for (j in 1:R[i] ){ > 126 Xij=CenteringV(X,Xjhbar[[i]][j,],n) > 127 Vij=t(W[[i]][,j]*Xij)%*%Xij/n11[[i]][j] > > 128 for (k in 1:q ){ > 129 for (l in 1:R[k]){ > > 130 Xkl=CenteringV(X,Xjhbar[[k]][l,],n) > 131 Vijkl=t(W[[i]][,j]*Xij)%*%(W[[k]][,l]*Xkl)/n > > 132 Vkl=t(W[[k]][,l]*Xkl)%*%Xkl/n11[[k]][l...

...alculation > > > > 119 # Calculation of Vn > > 120 X1=CenteringV(X,Xbar,n) > > 121 Vn=t(X1)%*%X1/n > > > > 122 ## Construction of Sigma > > 123 GSigma=matrix(0,p*sum(R),p*sum(R)) > > 124 for (i in 1:q ){ > > 125 for (j in 1:R[i] ){ > > 126 Xij=CenteringV(X,Xjhbar[[i]][j,],n) > > 127 Vij=t(W[[i]][,j]*Xij)%*%Xij/n11[[i]][j] > > > > 128 for (k in 1:q ){ > > 129 for (l in 1:R[k]){ > > > > 130 Xkl=CenteringV(X,Xjhbar[[k]][l,],n) > > 131 Vijkl=t(W[[i]][,j]*Xij)%*%(W[[k]][,l]*Xkl)/n > > > >...

...ource/blob/01374c3c367fa12f555fd354f735a6e16e5bd98e/src/library/base/R/dataframe.R#L1395 The error is thrown because the line attempts to set a subset of the rownames to NULL, which fails. R> options(error = recover) R> rbind(dfm.names, dfm) Error in rownames(value[[jj]])[ri] <- rownames(xij) : replacement has length zero Enter a frame number, or 0 to exit 1: rbind(dfm.names, dfm) 2: rbind(deparse.level, ...) Selection: 2 Called from: top level Browse[1]> rownames(value[[jj]]) [1] "a" "b" "c" NA NA NA Browse[1]> rownames(xij) NULL Browse[1]&gt...

Greetings, I would like to use some of the spatial statistics functions in R, but I am having trouble entering data. My data is already in a distance matrix format, not an X Y coordinate format (each Xij cell in the matrix represens the distance from point i to j). Does anyone know of a way to convert a distance matrix to a ppp object in spatstat, or an X,Y coordinate system for other packages? Thanks, Jesse [[alternative HTML version deleted]]

The compositional data xi=(x_i1, x_i2,..., x_in), for each fixed i , xij>0, and sum(xij)=1; I want to compare the mean( u_i) of several groups i.e. H0: u_1=u_2=...=u_N or Hj0: u_1j=u_2j=...=u_Nj Are there any ANOVA tpye tools to do this work in R? Thanks, WEN S Q [[alternative HTML version deleted]]