similar to: Error in eigen(a$hessian) : infinite or missing values in 'x'

Hi, I'm trying to estimate the parameters of a state space model of the following form measurement eq: z_t = a + b*y_t + eps_t transition eq y_t+h = (I -exp(-hL))theta + exp(-hL)y_t+ eta_{t+h}. The problem is that the distribution of the innovations of the transition equation depend on the previous value of the state variable. To be exact: y_t|y_{t-1} ~N(mu, Q_t) where Q is a diagonal

Dear R users, When running the program below I receive the following error message: fit <- optim(parm, objective, yt = tyield, hessian = TRUE) Error in as.vector(data) : no method for coercing this S4 class to a vector I can't figure out what the problem is exactly. I imagine that it has something to do with "tyield" being a matrix. Any help on explaining what's going on

Hi, Use the `auglag' function in "alabama" if you want to get the Hessian at convergence. This typically tends to perform better than `constrOptim.nl'. Also, `constrOptim.nl' does not compute the Hessian. You should not specify method="L-BFGS-B". The default method "BFGS" is better in this setting. Hope this helps, Ravi

Hello, This is my first post to the help request list, so I'm going to err on the side of giving too much information. I'm working on writing a simulation in which agents will make repeated production and exchange decisions with randomly chosen partners. The idea is, all agents can produce two goods which they want to consume, they choose a value t in [0,10] which sets their production

Hi, I would like to know what should I garantee about P and GGt in order to have F = Z %*% P %*% t(Z) + GGt always as a positive definite matrix. Being more precise: I am trying to find minimum likelihood parameters by using the function 'optim' to find the lowest value generated by $LogLik from the function 'fkf' (http://127.0.0.1:27262/library/FKF/html/fkf.html). The

Dear All, I am running a simulation to obtain coverage probability of Wald type confidence intervals for my parameter d in a function of two parameters (mu,d). I am optimizing it using "optim" method "L-BFGS-B" to obtain MLE. As, I want to invert the Hessian matrix to get Standard errors of the two parameter estimates. However, my Hessian matrix at times becomes

Hello, I am attempting to utilize the 'alabama' package to solve a constrained nonlinear optimization problem. The problem has both equality and inequality constraints (heq and hin functions are used). All constraints are smooth, i.e. I can differentiate easily to produce heq.jac and hin.jac functions. My initial solution is feasible; I am attempting to maximize a function, phi. As

Hi, I am testing code that is working successfully using constrOptim. I am replacing constrOptim with other solvers to compare benefits and performance. My belief was that, like constrOptim, auglag in the alabama package would eliminate beta vectors that failed the constraints prior to calling the objective function. These betas are not only not in the solution space but also cause

Dear R users, I am trying to carry out MLE of the time-varying CAPM using the FKF package. My approach so far has been to try and adapt the example given in the help file found using ?fkf which demonstrates the MLE of an ARMA(2,1) model. When I attempt to run my R code (given below) I get the following error: Error in fkf(a0 = sp$a0, P0 = sp$P0, dt = sp$dt, ct = sp$ct, Tt = sp$Tt, : Some of

Hi, I'll coded your example into R code: Table_A <- c('abc at gmail.com', 'John Chan', '0909') Table_A <- rbind(Table_A, c('bcd at yahoo.com', 'Tim Ma', '89089')) colnames(Table_A) <- c('Email', 'Name', 'Phone') Table_A Table_B <- c('abc at gmail.com', 'John Chan', 'M',

Dear all, I'd like to discuss about a possible bug in function StructTS of stats package. It seems that the function returns wrong value of the log-likelihood, as the added constant to the relevant part of the log-likelihood is misspecified. Here is an simple example: > data(Nile) > fit <- StructTS(Nile, type = "level") > fit$loglik [1] -367.5194 When computing the

Dear List, I'm trying to solve this simple optimization problem in R. The parameters are the exponents to the matrix mm. The constraints specify that each row of the parameter matrix should sum to 1 and their product to 0. I don't understand why the constraints are not satisfied at the solution. I must be misinterpreting how to specify the constrains somehow. library(alabama) ff <-

Dear all, I am running an Ecological Niche Factor Analysis in R but I am stuck with a problem. As soon as I ask the software to compute the ENFA, I get the following error message: Error in eigen(Se) : infinite or missing values in 'x' Does anyone know what could be wrong. I do not have missing values in my dataset. Please follow the codes I used for my analysis so far: library

To R programming experts, I am a undergraduate student, and now doing research personally. I apply diagonal bivariate poisson (R package "bivpois") with stochatics weighted function (refer to dixoncoles97 section 4.5 to 4.7). However I dont know how to fit this stochatical weighted function to the completed bivariate poisson model. I know that some other references for dynamic soccer

Dear Helper, I used "constrOptim.nl" and got the value of par. The estimations looks good even if the number of iterations is only 16. But the values of hessian and convergence are both "NULL". I tested the objective function and gradient function by "optim" and didn't see any problem there. With these functions, "optim" gives the convergence value

Hello, I want to perform a nonlinear curve fit in order to obtain parameter estimates from experimentally determined data (y in dependence of x), but with an implicit function, thus, a function of which I cannot isolate y on the left-hand side of the equation. As far as I understand, the functions I found up to now (nls, optim) all work only for explicit functions. My data looks like

Thanks - Peter, Eivind, Rui Sorry, I perhaps could not explain it properly in the first go. Trying to simplify it here with an example - Say I have two dataframes as below that are NOT equally-sized data frames (i.e., number of columns are different in each table): Table_A: Email Name Phone abc at gmail.com John Chan 0909 bcd at yahoo.com Tim Ma

  Dear Fellow R Users, I am experimenting right now the FKF package. I started by working out the first example included in the package and I am already confused. Would you offer some kind suggestions? What I want to do is to write down the state transition equation and the measurement equation explicitly. Following the first example: According to: dt <- matrix(0, nrow = 2) the state vector

Hi everyone, It's a very minor point, but could we ensure that eigen and La.eigen return a *matrix* for the "vectors" component of the list by including a "drop = FALSE", as specified in the help file, ie put list(values = z$values[ord], vectors = if (!only.values) z$vectors[, ord, drop = FALSE]) Thanks, Jonathan. --please do not edit the information

Dear all, It is not a R related problem rather than statistical/mathematical. However I am posting this query hoping that anyone can help me on this matter. My problem is to get the Geometrical Interpretation of Eigen value and Eigen vector of any square matrix. Can anyone give me a light on it? Thanks and regards, Arun [[alternative HTML version deleted]]