similar to: Kalman filter for a time series

> structSSM Is no longer part of KFAS. All you needed to do was: library(KFAS) ?KFAS and you would have seen that if you went to the index. A structural state space model is now built up from its components, much like in LM. Look at; ?SSModel -Roy > On Jul 29, 2017, at 9:26 PM, Staff <rbertematti at gmail.com> wrote: > > I found an example at >

On 2017-07-29 11:26 PM, Staff wrote: > I found an example at > http://www.bearcave.com/finance/random_r_hacks/kalman_smooth.html That example is signed by "Ian Kaplan". There's a box at the bottom of the page for you to email him. > shown > below. But it seems the structSSM function has been removed from KFAS > library or it never was part of

> On Jul 30, 2017, at 5:10 AM, Spencer Graves <spencer.graves at effectivedefense.org> wrote: > > > > On 2017-07-29 11:26 PM, Staff wrote: >> I found an example at >> http://www.bearcave.com/finance/random_r_hacks/kalman_smooth.html > > That example is signed by "Ian Kaplan". There's a box at the bottom of the page for you to email

Dear all, I would like to ask how my data set contains problems. Here is what I have done. SandP = read.csv("Price.csv") library("forecast") auto.arima(SandP) and R shewed this to me Error in model.frame.default(formula = x ~ 1, drop.unused.levels = TRUE) : invalid type (list) for variable 'x' In my data set SandP it contains 1 column of the daily

Hello: What's the preferred way to link to package documentation from a vignette using markdown? My current draft includes "[cumsum](https://stat.ethz.ch/R-manual/R-devel/library/base/html/cumsum.html)" to link to the help page for cusum{base} and "[KFAS](https://rweb.crmda.ku.edu/cran/web/packages/KFAS/KFAS.pdf)" to link to the pdf documentation for

Hi, Duncan: On 10/18/2015 8:18 PM, Duncan Murdoch wrote: > On 18/10/2015 5:51 PM, Spencer Graves wrote: >> Hello: >> >> >> What's the preferred way to link to package documentation from a >> vignette using markdown? >> >> >> My current draft includes >>

Hi Everyone, I'm trying to write selfStart non-linear models for use with nls. In these models some combinations of parameter values are illegal; the function value is undefined. That's OK when calling the function directly [e.g. SSmodel(x, pars...)]; I return an appropriate non-value such as NA or Inf. However, when called from nls [e.g. nls(y~SSmodel(x, pars...), ...)] those

Hi Everyone, I posted this a couple of weeks ago with no responses. My interface (via gmane) seemed a bit flakey at the time, so I'm venturing to repost with some additional information. I'm trying to write selfStart non-linear models for use with nls. In these models some combinations of parameter values are illegal; the function value is undefined. That's OK when calling the

CRAN (and crantastic) updates this week New packages ------------ Updated packages ---------------- New reviews ----------- This email provided as a service for the R community by http://crantastic.org. Like it? Hate it? Please let us know: cranatic at gmail.com.

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 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 all, I am pleased to announce the CRAN release of a new package called 'KFAS' - Kalman filter and smoother. The package KFAS contains functions of multivariate Kalman filter, smoother, simulation smoother and forecasting. It uses univariate approach algorithm (aka sequential processing), which is faster than normal method, and it also allows mean square prediction error matrix Ft to

Dear all, I am pleased to announce the CRAN release of a new package called 'KFAS' - Kalman filter and smoother. The package KFAS contains functions of multivariate Kalman filter, smoother, simulation smoother and forecasting. It uses univariate approach algorithm (aka sequential processing), which is faster than normal method, and it also allows mean square prediction error matrix Ft to

CRAN (and crantastic) updates this week New packages ------------ * Bergm (1.0) Alberto Caimo http://crantastic.org/packages/Bergm Functions implementing Bayesian estimation for exponential random graph models via exchange algorithm Updated packages ---------------- lmtest (0.9-26), logcondens (1.3.5), MTSKNN (0.0-4), pmml (1.2.21), r2lUniv (0.9.4), rattle (2.5.11), rgdal (0.6-23),

hello, i am new to R and trying to calculate the beta coefficient for standard linear regression for a series of randomly generated numbers. I have created this loop, but it runs really slow, is there a way to improve it? #number of simulations n.k<-999 #create the matrix for regression coefficients generated from #random data beta<-matrix(0,1,n.k+1) e<-matrix(0,tslength,n.k+1) for(k

Dear All, I am trying to fit a structural time series model using the StructTS function (package stats) with only 2 seasons (summer and winter). More than 2 seasons work fine but with 2 seasons I get this error: > fit <- StructTS(y.ts, type="BSM") Error in T[cbind(ind + 1L, ind)] <- 1 : subscript out of bounds I have looked at Prof. Ripley's 2002 RNews article but cannot

Hello, I would like use Kalman filter for estimating parameters of a stochastic model. I have developed the state space model but I don’t know the correct way use Kalman filter for parameter estimation. Has anybody experience in work with Kalman filter in R. I don’t know the correct function. Maybe it is - KalmanLike; but what is the correct Input? - tsmooth? -

Hello everybody, I am writing a review paper about State Space models in R, and I would like to cover as many packages as I reasonably can. So far I am familiar with the following tools to deal with SS models: * StructTS, Kalman* (in stats) * packages dse[1-2] * package sspir * package dlm I would like to have some input from users who work with SS models: are there any other packages for SS

CRAN (and crantastic) updates this week New packages ------------ * bdoc (1.0) Michael Anderson http://crantastic.org/packages/bdoc This package contains a function that will classify DNA barcodes as well as a few test and reference data sets. * bdsmatrix (1.0) Terry Therneau http://crantastic.org/packages/bdsmatrix This is a special case of sparse matrices, used by coxme and

On 18/10/2015 5:51 PM, Spencer Graves wrote: > Hello: > > > What's the preferred way to link to package documentation from a > vignette using markdown? > > > My current draft includes > "[cumsum](https://stat.ethz.ch/R-manual/R-devel/library/base/html/cumsum.html)" > to link to the help page for cusum{base} and >