mixpp Class List

Here are the classes, structs, unions and interfaces with brief descriptions:
bilinfnClass representing function $f(x,u) = Ax+Bu$
BMBayesian Model of the world, i.e. all uncertainty is modeled by probabilities
BMcondConditional Bayesian Filter
constfnClass representing function $f(x) = a$, here rv is empty
diffbifnClass representing a differentiable function of two variables $f(x,u)$
DSAbstract class for discrete-time sources of data
eEFGeneral conjugate exponential family posterior density
eEmpWeighted empirical density
egammaGamma posterior density
EKF< sq_T >Extended Kalman Filter
emixWeighted mixture of epdfs with external owned components
enorm< sq_T >Gaussian density with positive definite (decomposed) covariance matrix
epdfProbability density function with numerical statistics, e.g. posterior density
euniUniform distributed density on a rectangular support
fncClass representing function $f(x)$ of variable $x$ represented by rv
fsqmatFake sqmat. This class maps sqmat operations to operations on full matrix
itpp::Gamma_RNGGamma distribution
Kalman< sq_T >Kalman filter with covariance matrices in square root form
KalmanFullBasic Kalman filter with full matrices (education purpose only)! Will be deleted soon!
KFcondQRKalman Filter with conditional diagonal matrices R and Q
linfnClass representing function $f(x) = Ax+B$
MemDSClass representing off-line data stored in memory
mgammaGamma random walk
mlnorm< sq_T >Normal distributed linear function with linear function of mean value;
mpdfConditional probability density, e.g. modeling some dependencies
MPF< BM_T >Marginalized Particle filter
PFTrivial particle filter with proposal density equal to parameter evolution model
RVClass representing variables, most often random variables
sqmatVirtual class for representation of double symmetric matrices in square-root form

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