similar to: Different length of objects

Hello Tyler, I rephrase my previous mail, as follows: In your example, T_i = X1:X2:X3. Let F_j = X3. (The numerical variables X1 and X2 are not encoded at all.) Then T_{i(j)} = X1:X2, which in the example is dropped from the model. Hence the X3 in T_i must be encoded by dummy variables, as indeed it is. Arie On Thu, Nov 2, 2017 at 4:11 PM, Tyler <tylermw at gmail.com> wrote: > Hi

Hello Tyler, You write that you understand what I am saying. However, I am now at loss about what exactly is the problem with the behavior of R. Here is a script which reproduces your experiments with three variables (excluding the full model): m=expand.grid(X1=c(1,-1),X2=c(1,-1),X3=c("A","B","C")) model.matrix(~(X1+X2+X3)^3-X1:X3,data=m)

Hello Tyler, Thank you for searching for, and finding, the basic description of the behavior of R in this matter. I think your example is in agreement with the book. But let me first note the following. You write: "F_j refers to a factor (variable) in a model and not a categorical factor". However: "a factor is a vector object used to specify a discrete classification"

Hai I'm Dee. I'm trying to write var data from these codes inside excel file. My directory to store the data is *D:\FYP\image* . these are my codes, can you help give an advice or idea with my problem: l*ibrary("biOps") library("waveslim") library("xlsReadWrite") x <- readTiff("D:\\FYP\\image\\SignatureImage\\user186g1.tif") y <-

Hello Tyler, I want to bring to your attention the following document: "What happens if you omit the main effect in a regression model with an interaction?" (https://stats.idre.ucla.edu/stata/faq/what-happens-if-you-omit-the-main-effect-in-a-regression-model-with-an-interaction). This gives a useful review of the problem. Your example is Case 2: a continuous and a categorical regressor.

Hai, I'm trying to write these var output data from these codes inside excel file. My directory to store the data is /D:\FYP\image / but receive an error message : /Error in write.xls(mydata, "D:\\FYP\\image.mydata.xls") : object 'mydata' not found/ these are my codes, can you help give an advice or idea with my problem: /library("biOps")

Hola eRReros. Os lo explico con un ejemplo: # Cargamos los paquetes y el ejemplo install.packages("SPEI") library("SPEI") data(wichita) # los primeros 12 datos head(wichita,12) # mi subset de los primeros 12 datos meu<-wichita[c(1:12),] meu # como veis los valores de TMED son iguales en ambos dataframes. # ahora viene el problema # calculamos

I have the following xts objetct "temp" > str(temp) An ?xts? object from 2010-12-26 to 2011-03-05 containing: Data: num [1:70, 1] 2.95 0.852 -0.139 1.347 2.485 ... - attr(*, "dimnames")=List of 2 ..$ : NULL ..$ : chr "t_n" Indexed by objects of class: [POSIXct,POSIXt] TZ: GMT xts Attributes: NULL > temp t_n 2010-12-26

Dear All, I'm having just a little terminology problem, relating the language used in the Hosmer and Lemeshow text on Applied Survival Analysis to that of the help that comes with the survival package. I am trying to back out the values for the baseline hazard, h_o(t_i), for each event time or observation time. Now survfit(fit)$surv gives me the value of the survival function, S(t_i|X_i,B),

Dear R-list members, I've had a hard time trying to solve a non-linear system (nls) of equations which structure for the equation i, i=1,...,4, is as follows: f_i(d_1,d_2,d_3,d_4)-k_i(l,m,s) = 0 (1) In the expression above, both f_i and k_i are known functions and l, m and s are known constants. I would like to estimate the vector d=(d_1,d_2,d_3,d_4) which is solution

Hello, I am new to R and I am trying to estimate a discrete model with three choices. I am stuck at a point and cannot find a solution. I have probability functions for occurrence of these choices, and then I build the likelihood functions associated to these choices and finally I build the general log-likelihood function. There are four parameters in the model, three of them are associated to

Hello, i have coded the following loglikelihood-function # Log-Likelihood-Funktion loglik_jm<-function(N,phi,t) { n<-length(t) i<-seq(along=t) s1<-sum(log(N-(i-1))) s2<-phi*sum((N-(i-1))*t[i]) n*log(phi)+s1-s2 } # the data t<-c(7,11,8,10,15,22,20,25,28,35) # now i want to do a 3d-plot and a contourplot in order to see at which values of N and phi the loglikelihood

Dear R users, I have been trying to solve for mle's of a function that involves an integral and I keep getting an error. I created an example to work on first and even the simple example doesn't give me the mle's. I am getting the error "Error in integrate(integrand, 0, Inf) : non-finite function value". I divided my likelihood function into two parts, one part involves

Hi, I have a right-censored (positive) random variable (e.g. failure times subject to right censoring) that is observed for N subjects: Y_i, I = 1, 2, ..., N. Note that Y_i = min(T_i, C_i), where T_i is the true failure time and C_i is the censored time. Let us assume that C_i is independent of T_i. Now, I would like to generate another random variable U_i, I = 1, 2, ..., N, which is

I would like to code the following in R: a1(b1+b2+b3) + a2(b1+b3+b4) + a3(b1+b2+b4) + a4(b1+b2+b3) or in summation notation: sum_{i=1, j\neq i}^{4} a_i * b_i I realise this is the same as: sum_{i=1, j=1}^{4} a_i * b_i - sum_{i=j} a_i * b_i would appreciate some help. Thank you. -- View this message in context: http://r.789695.n4.nabble.com/summation-coding-tp4646678.html Sent from the R

Hi Everybody I want to print a latex table containing math characters in the column heading These are the formulae I want to use as column headings. It prints OK from TeX $\sum_{i}\sum_{j}C_{P,i,j,y}\times\mathit{FC}_{i}$, $XU_{alt,y}$, $n$, $\bar{C}_{P,y}$ My plan was to create a character vector with these and later rbind the values to them. When I create the vector like:

Hi, I'm trying to subset a list which contains variable length vectors. What I want to do is extract (eg.) the 3rd item in each vector (with length >= 3). At the moment I'm using sapply(list.of.vectors, function(x) {x[3]}). The problem with this is that sapply returns a list of the same length of list.of.vectors so I end up with a whole lot of null entries from those vectors

Dear R users, I?m a graduate students and in my master thesis I must obtain the values of the parameters x_i which maximize this Multinomial log?likelihood function log(n!)-sum_{i=1]^4 log(n_i!)+sum_ {i=1}^4 n_i log(x_i) under the following constraints: a) sum_i x_i=1, x_i>=0, b) x_1<=x_2+x_3+x_4 c)x_2<=x_3+x_4 I have been using the ?ConstrOptim? R-function with the instructions

Hello, I want to solve a nonlinear 3SLS problem with "nlsystemfit()". The equations are of the form y_it = f_i(x,t,theta) The functions f_i(.) have to be formulated as R-functions. When invoking "nlsystemfit()" I get the error Error in deriv.formula(eqns[[i]], names(parmnames)) : Function 'f1' is not in the derivatives table

Dear all, Could any one please tell me the exact formula R uses to calculate the sample size for one-sample and two-sample t-tests? Thanks, Caimiao [[alternative HTML version deleted]]