• EnKF

  • Referenced in 441 articles [sw02066]
  • model states to represent the error statistics of the model estimate, it applies ensemble integrations ... predict the error statistics forward in time, and it uses an analysis scheme which operates ... directly on the ensemble of model states when observations are assimilated. The EnKF has proven...
  • VanHuffel

  • Referenced in 231 articles [sw05243]
  • also known as the errors-in-variables model. The renewed interest in the TLS method...
  • spdep

  • Referenced in 39 articles [sw04578]
  • spdep: Spatial dependence: weighting schemes, statistics and models , A collection of functions to create spatial ... spatial simultaneous autoregressive (SAR) lag and error models, impact measures for lag models, weighted ... Moran eigenvector spatial filtering, GM SAR error models, and generalized spatial two stage least squares...
  • HyTech

  • Referenced in 333 articles [sw04125]
  • symbolic model checking. If the verification fails, then HyTech generates a diagnostic error trace...
  • Bandera

  • Referenced in 134 articles [sw07663]
  • property being checked. When a model-checker produces an error trail, Bandera renders the error...
  • BLINPLUS

  • Referenced in 34 articles [sw37140]
  • blinplus corrects for measurement error in one or more model covariates logistic regression coefficients, their ... standard errors, and odds ratios and 95% confidence intervals for a biologically meaningful difference specified ... user (the ”weights”). Regression model parameters from Cox models (PROC PHREG) and linear regression models ... required to empirically characterize the measurement error model. Options are given for main study/external validation...
  • decon

  • Referenced in 22 articles [sw11088]
  • decon: Deconvolution Estimation in Measurement Error Models. This package contains a collection of functions ... kernel methods. We focus two measurement error models in the package: (1) an additive measurement ... error model, where the goal is to estimate the density or distribution function from contaminated ... Deconvolution estimation in measurement error models: The R package decon. Journal of Statistical Software...
  • DAISY

  • Referenced in 54 articles [sw09059]
  • ideal conditions (noise-free observations and error-free model structure). Of course, determining...
  • OSCAR

  • Referenced in 58 articles [sw03026]
  • techniques in terms of both prediction error and model complexity, while yielding the additional grouping...
  • goodwin.f77

  • Referenced in 22 articles [sw37144]
  • Application to logistic-normal models. Journal of the American Statistical Association ... current interest, including binary measurement-error models and the analysis of teratogenicity experiments. Analytic intractability ... used with multiple covariate regression models of the logistic-normal form. We conducted a simulation ... risk in the logistic-normal measurement-error model. Using standard subroutines to maximize the likelihood...
  • IFISS

  • Referenced in 258 articles [sw04398]
  • Algorithm 866: IFISS, a Matlab toolbox for modelling incompressible flow. IFISS is a graphical Matlab ... mixed finite element methods and a posteriori error estimation of the computed solutions. The package ... equation systems that arise in incompressible flow modelling. A unique feature of the package...
  • PROC GENMOD

  • Referenced in 34 articles [sw11741]
  • models. These include classical linear models with normal errors, logistic and probit models for binary...
  • System Identification Toolbox

  • Referenced in 179 articles [sw05686]
  • parametric, subspace-based, and prediction-error algorithms coupled (in the latter case) with either MIMO ... state space or MISO polynomial model structures. A key feature of the software...
  • GeoDa

  • Referenced in 19 articles [sw08282]
  • spatial lag model and the spatial error model, both estimated by maximum likelihood, are included...
  • ODRPACK

  • Referenced in 21 articles [sw00649]
  • surface fitting, and to measurement error models in statistics. ODRPACK can handle both explicit ... implicit models, and will easily accommodate complex and other types of multiresponse data. The algorithm ... finite difference derivatives, and contains extensive error checking and report generating facilities...
  • gcmr

  • Referenced in 31 articles [sw07433]
  • extension of traditional linear regression models with normal correlated errors. Any kind of continuous, discrete ... allowed. Dependence is conveniently modelled in terms of multivariate normal errors. Inference is performed through ... validating the adequacy of the assumed multivariate model. Methodology is implemented in a R package...
  • VAMPnets

  • Referenced in 19 articles [sw32927]
  • step will lead to large modeling errors. Here we employ the variational approach for Markov ... better than state-of-the art Markov modeling methods and provides easily interpretable few-state...
  • TAMC

  • Referenced in 72 articles [sw07198]
  • more sophisticated model is extremely time consuming and subject to errors. Hence, automatic generation ... article, is the tangent linear and adjoint model compiler...
  • sandwich

  • Referenced in 36 articles [sw04486]
  • sandwich: Robust Covariance Matrix Estimators , Model-robust standard error estimators for cross-sectional, time series...
  • Zinc

  • Referenced in 26 articles [sw08334]
  • important characteristics. First, Zinc allows specification of models using a natural mathematical-like notation ... checking which allows early detection of errors in models. Finally, perhaps the main novelty...