• unmarked

  • Referenced in 8 articles [sw14405]
  • observation processes can be modeled as functions of covariates...
  • LIBRA

  • Referenced in 28 articles [sw10553]
  • library contains functions for univariate location, scale and skewness, multivariate location and covariance estimation ... quantiles. For comparison also several non-robust functions are included. Many graphical tools are provided...
  • LatticeKrig

  • Referenced in 4 articles [sw15594]
  • comparable to standard families of covariance functions. Using a large number of basis functions allows ... with a small nugget variance.) Moreover, the covariance model for this method can approximate ... estimating covariance parameters. This is accomplished through compactly supported basis functions and a Markov random ... geometries simple where only a few specific functions need to be added with most...
  • spTest

  • Referenced in 3 articles [sw19766]
  • words, whether or not the spatial covariance function is isotropic. Isotropy implies that spatial dependence ... function of only the distance and not the direction of the spatial separation between sampling ... desirable. To avoid specification of the covariance function, a number of nonparametric tests of isotropy...
  • multtest

  • Referenced in 22 articles [sw08262]
  • zero and variance covariance matrix derived from the vector influence function. Results are reported...
  • mvis

  • Referenced in 10 articles [sw37353]
  • single variable as a function of several covariates, each with complete data. micombine fits...
  • Rfam

  • Referenced in 33 articles [sw04637]
  • covariance models (CMs). The families in Rfam break down into three broad functional classes...
  • GRAVSOFT

  • Referenced in 4 articles [sw07999]
  • determination of the empirical covariance function and its analytic modelling and geoid determination using least...
  • BFDA

  • Referenced in 2 articles [sw14769]
  • smoothing functional data and estimating mean-covariance functions simultaneously and nonparametricaly, with the assumptions ... Inverse-Whishart process for the covariance function. An option of approximating the Bayesian inference process ... functional data and estimates the mean-covariance functions in a nonparametric way; (2) efficiently deals...
  • mcglm

  • Referenced in 5 articles [sw23203]
  • structures defined in terms of a covariance link function combined with a matrix linear predictor ... based on quasi-likelihood and Pearson estimating functions, using only second-moment assumptions. This provides ... different types of response variables and covariance structures, including multivariate extensions of repeated measures, time ... fitting McGLMs similar to the glm() R function...
  • HGLMMM

  • Referenced in 6 articles [sw08092]
  • overdispersion) can be modeled as a function of covariates. Overdispersion parameter can be fixed...
  • KBAL

  • Referenced in 3 articles [sw36072]
  • user to choose what functions of the covariates must be balanced ... biased if any function of the covariates influencing the outcome has a different mean ... large class of smooth functions of the covariates, and (2) approximately equalize the multivariate densities...
  • extRemes

  • Referenced in 9 articles [sw23856]
  • completely redesigned from previous versions. The functions primarily provide utilities for implementing univariate EVA, with ... including the incorporation of covariates, as well as some functionality for assessing bivariate tail dependence...
  • covatest

  • Referenced in 1 article [sw33821]
  • Tests on Properties of Space-Time Covariance Functions. Tests on properties of space-time covariance ... Moreover tests on some classes of covariance functions, such that the classes of product ... some classes of space-time covariance function models and Cappello ... selecting a class of space-time covariance functions
  • BayesNSGP

  • Referenced in 2 articles [sw30769]
  • Gaussian Process Models. Enables off-the-shelf functionality for fully Bayesian, nonstationary Gaussian process modeling ... involves a closed-form, convolution-based covariance function with spatially-varying parameters; these parameter processes ... specified either deterministically (using covariates or basis functions) or stochastically (using approximate Gaussian processes). Stationary...
  • msm

  • Referenced in 49 articles [sw08096]
  • hidden Markov models in continuous time. Functions for fitting general continuous-time Markov and hidden ... process can be modelled in terms of covariates, which may be constant or piecewise-constant...
  • comproc

  • Referenced in 4 articles [sw37484]
  • among controls, we present a method for covariate adjustment. For factors that affect discrimination ... modelling the ROC curve as a function of covariates. Finally, for factors that contribute...
  • party

  • Referenced in 27 articles [sw07330]
  • variables and arbitrary measurement scales of the covariates. Based on conditional inference trees, cforest() provides ... implementation of Breiman’s random forests. The function mob() implements an algorithm for recursive partitioning...
  • SAFD

  • Referenced in 14 articles [sw14547]
  • fuzzy numbers). In particular, the package contains functions for the basic operations on the class ... variance, sample covariance, and the Dempster-Shafer (levelwise) histogram. Moreover a function to simulate fuzzy...
  • face

  • Referenced in 3 articles [sw23648]
  • package face: Fast Covariance Estimation for Sparse Functional Data. Implementation of the Fast Covariance Estimation...