Internal functions in the PSM-package.

Description

Internal functions in the PSM-package.

Usage

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
APL.KF(THETA, Model, Pop.Data, LB = NULL, UB = NULL, GUIFlag = 0, longOutput = FALSE,
       fast=TRUE,Linear=NULL)
APL.KF.gr(THETA, Model, Pop.Data, LB = NULL, UB = NULL, GradSTEP = 1e-04, GUIFlag = 0,
          fast=TRUE,Linear=NULL)
APL.KF.individualloop(theta, OMEGA, Model, Data, GUIFlag = 0, fast=TRUE,Linear)
CutThirdDim(a)
ExtKalmanFilter(phi, Model, Data, outputInternals = FALSE)
ExtKalmanSmoother(phi, Model, Data)
IndividualLL.KF(eta, theta, OMEGA, Model, Data, fast=TRUE,Linear=NULL)
IndividualLL.KF.gr(eta, theta, OMEGA, Model, Data, GradSTEP = 1e-04, GUIFlag = 0,
                   fast=TRUE,Linear=NULL)
LinKalmanFilter(phi, Model, Data, echo = FALSE, outputInternals = FALSE, fast=TRUE)
LinKalmanSmoother(phi, Model, Data)
ModelCheck(Model, Data, Par,DataHasY=TRUE)
logit(x, xmin, xmax)
invlogit(y, xmin, xmax)

Details

APK.KF

evaluates the population likelihood function.

APK.KF.gr

evaluates the gradient of APL.KF.

APL.KF.individualloop

contains the innner loop over individuals for APL.KF.

CutThirdDim

removes third and higher dimensions of dim-attribute for an array and thus creating a matrix.

ExtKalmanFilter

Performs a Extended Kalman filtering.

ExtKalmanSmoother

performs a non-linear Kalman smoothing.

IndividualLL.KF

evaluates the indivdual neg. log-likelihood function.

IndividualLL.KF.gr

evaluates the gradient of the indivdual neg. log-likelihood function.

LinKalmanFilter

performs a linear Kalman filtering.

LinKalmanSmoother

performs a linear Kalman smoothing.

ModelCheck

checks for dimensionalities and model objects. Furthermore it tests the Model objects and the dimensions in the Data set.

logit

gives logit transformation of a vector.

invlogit

gives invlogit transformation of a vector.

Author(s)

Stig B. Mortensen and S<f8>ren Klim

See Also

PSM