• KernSmooth

• Referenced in 1018 articles [sw04586]
• sets without the imposition of a parametric model. The main goal of this book...

• survival

• Referenced in 201 articles [sw04364]
• descriptive statistics, two-sample tests, parametric accelerated failure models, Cox model. Delayed entry (truncation) allowed ... models; interval censoring for parametric models. Case-cohort designs...

• bootlib

• Referenced in 461 articles [sw40642]
• with single samples from parametric and nonparametric models. Chapter 3 extends the basic ideas...

• System Identification Toolbox

• Referenced in 179 articles [sw05686]
• supported. These include the use of non-parametric, subspace-based, and prediction-error algorithms coupled ... either MIMO state space or MISO polynomial model structures. A key feature of the software ... models, the use of non-standard model parametrizations, and the employment of Expectation Maximization...

• GMRFLib

• Referenced in 338 articles [sw06641]
• data, spatio-temporal models, graphical models, and semi-parametric statistics. With so many applications ... GMRFs in complex hierarchical models, in which statistical inference is only possible using Markov Chain...

• np

• Referenced in 103 articles [sw10543]
• specification tests for parametric mean regression models and parametric quantile regression models, among others...

• quantreg

• Referenced in 162 articles [sw04356]
• nonlinear parametric and non-parametric (total variation penalized) models for conditional quantiles of a univariate...

• Church

• Referenced in 55 articles [sw08946]
• processes. Church is based on the Lisp model of lambda calculus, containing a pure Lisp ... simple description of many complex non-parametric models. We illustrate language features through several examples ... planning by inference, and various non-parametric clustering models. Finally, we show how to implement...

• SemiPar

• Referenced in 761 articles [sw07116]
• viewed as a relatively simple extension of parametric regression and treat the two together. They ... based on penalized regression splines and mixed models. Every model in this book...

• CONTSID

• Referenced in 37 articles [sw14945]
• testing and evaluating these data-based modelling techniques. The CONTSID toolbox was first released ... identifying linear dynamic continuous-time parametric models from measured input/output sampled data; it provides transfer...

• multcomp

• Referenced in 36 articles [sw10485]
• intervals for general linear hypotheses in parametric models, including linear, generalized linear, linear mixed effects...

• BEEM

• Referenced in 30 articles [sw09815]
• benchmark set includes more than 50 parametrized models (300 concrete instances) together with their correctness...

• frailtypack

• Referenced in 44 articles [sw06070]
• frailtypack: General Frailty models using a semi_parametric penalized likelihood estimation or a parametric estimation ... also a parametric estimation. 1) A shared gamma frailty model and Cox proportional hazard model...

• party

• Referenced in 28 articles [sw07330]
• regression models into a well defined theory of conditional inference procedures. This non-parametric class ... algorithm for recursive partitioning based on parametric models (e.g. linear models, GLMs or survival regression...

• flexsurv

• Referenced in 20 articles [sw15470]
• Survival and Multi-State Models. Flexible parametric models for time-to-event data, including ... Parmar spline model, generalized gamma and generalized F distributions. Any user-defined parametric distribution ... fitting and predicting from fully parametric multi-state models...

• DPpackage

• Referenced in 72 articles [sw10495]
• requires the relaxation of parametric assumptions in order to gain modeling flexibility and robustness against...

• spdep

• Referenced in 39 articles [sw04578]
• unweighted SAR and CAR spatial regression models, semi-parametric and Moran eigenvector spatial filtering...

• MatchIt

• Referenced in 17 articles [sw10538]
• King, and Stuart (2007) for improving parametric statistical models by preprocessing data with nonparametric matching ... hard-to-justify, but commonly made, statistical modeling assumptions. The software also easily fits into ... with MatchIt, researchers can use whatever parametric model they would have used without MatchIt...

• lmtest

• Referenced in 19 articles [sw04478]
• some generic tools for inference in parametric models are provided...

• Rhinoceros

• Referenced in 19 articles [sw07518]
• toolpath generation directly in Rhino. Like many modeling applications, Rhino also features a scripting language ... avant-garde architects are using parametric modeling tools, like Grasshopper. Rhino’s increasing popularity...