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r-coxridge
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A package for fitting Cox models with penalized ridge-type partial likelihood. The package includes functions for fitting simple Cox models with all covariates controlled by a ridge penalty. The weight of the penalty is optimised by using a REML type-algorithm. Models with time varying effects of the covariates can also be fitted. Some of the covariates may be allowed to be fixed and thus not controlled by the penalty. There are three different penalty functions, ridge, dynamic and weighted dynamic. Time varying effects can be fitted without the need of an expanded dataset.
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2023-06-16 |
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r-addt
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Accelerated destructive degradation tests (ADDT) are often used to collect necessary data for assessing the long-term properties of polymeric materials. Based on the collected data, a thermal index (TI) is estimated. The TI can be useful for material rating and comparison. This package implements the traditional method based on the least-squares method, the parametric method based on maximum likelihood estimation, and the semiparametric method based on spline methods, and the corresponding methods for estimating TI for polymeric materials. The traditional approach is a two-step approach that is currently used in industrial standards, while the parametric method is widely used in the statistical literature. The semiparametric method is newly developed. Both the parametric and semiparametric approaches allow one to do statistical inference such as quantifying uncertainties in estimation, hypothesis testing, and predictions. Publicly available datasets are provided illustrations. More details can be found in Jin et al. (2017).
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2023-06-16 |
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r-crf
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Implements modeling and computational tools for conditional random fields (CRF) model as well as other probabilistic undirected graphical models of discrete data with pairwise and unary potentials.
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2023-06-16 |
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r-covsep
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Functions for testing if the covariance structure of 2-dimensional data (e.g. samples of surfaces X_i = X_i(s,t)) is separable, i.e. if covariance(X) = C_1 x C_2. A complete descriptions of the implemented tests can be found in the paper Aston, John A. D.; Pigoli, Davide; Tavakoli, Shahin. Tests for separability in nonparametric covariance operators of random surfaces. Ann. Statist. 45 (2017), no. 4, 1431--1461. <doi:10.1214/16-AOS1495> <https://projecteuclid.org/euclid.aos/1498636862> <arXiv:1505.02023>.
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2023-06-16 |
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r-corrmixed
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In clinical practice and research settings in medicine and the behavioral sciences, it is often of interest to quantify the correlation of a continuous endpoint that was repeatedly measured (e.g., test-retest correlations, ICC, etc.). This package allows for estimating these correlations based on mixed-effects models. Part of this software has been developed using funding provided from the European Union's 7th Framework Programme for research, technological development and demonstration under Grant Agreement no 602552.
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2023-06-16 |
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r-correctedfdr
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There are many estimators of false discovery rate. In this package we compute the Nonlocal False Discovery Rate (NFDR) and the estimators of local false discovery rate: Corrected False discovery Rate (CFDR), Re-ranked False Discovery rate (RFDR) and the blended estimator. Bickel, D. R. (2016) <http://hdl.handle.net/10393/34277>.
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2023-06-16 |
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r-copuladata
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Data sets used for copula modeling in addition to those in the package 'copula'. These include a random subsample from the US National Education Longitudinal Study (NELS) of 1988 and nursing home data from Wisconsin.
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2023-06-16 |
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r-conting
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Bayesian analysis of complete and incomplete contingency tables.
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2023-06-16 |
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r-compoisson
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Provides routines for density and moments of the Conway-Maxwell-Poisson distribution as well as functions for fitting the COM-Poisson model for over/under-dispersed count data.
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2023-06-16 |
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r-complexity
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Allows for the easy computation of complexity: the proportion of the parameter space in line with the hypothesis by chance. The package comes with a Shiny application in which the calculations can be conducted as well.
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2023-06-16 |
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r-covbm
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Allows Brownian motion, fractional Brownian motion, and integrated Ornstein-Uhlenbeck process components to be added to linear and non-linear mixed effects models using the structures and methods of the 'nlme' package.
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2023-06-16 |
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r-coranking
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Calculates the co-ranking matrix to assess the quality of a dimensionality reduction.
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2023-06-16 |
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r-decido
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Provides constrained triangulation of polygons. Ear cutting (or ear clipping) applies constrained triangulation by successively 'cutting' triangles from a polygon defined by path/s. Holes are supported by introducing a bridge segment between polygon paths. This package wraps the 'header-only' library 'earcut.hpp' <https://github.com/mapbox/earcut.hpp.git> which includes a reference to the method used by Held, M. (2001) <doi:10.1007/s00453-001-0028-4>.
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2023-06-16 |
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r-cxhull
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Computes the convex hull in arbitrary dimension, based on the Qhull library (<http://www.qhull.org>). The package provides a complete description of the convex hull: edges, ridges, facets, adjacencies. Triangulation is optional.
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2023-06-16 |
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r-ctrlgene
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A simple way to assess the stability of candidate housekeeping genes is implemented in this package.
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2023-06-16 |
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r-cstar
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Functions that allow a researcher to examine the robustness of the substantive significance of their findings. Implements ideas set out in Esarey and Danneman (2014).
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2023-06-16 |
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r-cpprouting
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Calculation of distances, shortest paths and isochrones on weighted graphs using several variants of Dijkstra algorithm. Proposed algorithms are unidirectional Dijkstra (Dijkstra, E. W. (1959) <doi:10.1007/BF01386390>), bidirectional Dijkstra (Goldberg, Andrew & Fonseca F. Werneck, Renato (2005) <https://pdfs.semanticscholar.org/0761/18dfbe1d5a220f6ac59b4de4ad07b50283ac.pdf>), A* search (P. E. Hart, N. J. Nilsson et B. Raphael (1968) <doi:10.1109/TSSC.1968.300136>), new bidirectional A* (Pijls & Post (2009) <http://repub.eur.nl/pub/16100/ei2009-10.pdf>).
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2023-06-16 |
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r-controltest
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Nonparametric two-sample procedure for comparing survival quantiles.
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2023-06-16 |
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r-conake
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Continuous smoothing of probability density function on a compact or semi-infinite support is performed using four continuous associated kernels: extended beta, gamma, lognormal and reciprocal inverse Gaussian. The cross-validation technique is also implemented for bandwidth selection.
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2023-06-16 |
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r-chor
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Learning the structure of graphical models from datasets with thousands of variables. More information about the research papers detailing the theory behind Chordalysis is available at <http://www.francois-petitjean.com/Research> (KDD 2016, SDM 2015, ICDM 2014, ICDM 2013). The R package development site is <https://github.com/HerrmannM/Monash-ChoR>.
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2023-06-16 |
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r-cusp
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Cobb's maximum likelihood method for cusp-catastrophe modeling (Grasman, van der Maas, & Wagenmakers, 2009, JSS, 32:8; Cobb, L, 1981, Behavioral Science, 26:1, 75--78). Includes a cusp() function for model fitting, and several utility functions for plotting, and for comparing the model to linear regression and logistic curve models.
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2023-06-16 |
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r-crseeventstudy
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Based on Dutta et al. (2018) <doi:10.1016/j.jempfin.2018.02.004>, this package provides their standardized test for abnormal returns in long-horizon event studies. The methods used improve the major weaknesses of size, power, and robustness of long-run statistical tests described in Kothari/Warner (2007) <doi:10.1016/B978-0-444-53265-7.50015-9>. Abnormal returns are weighted by their statistical precision (i.e., standard deviation), resulting in abnormal standardized returns. This procedure efficiently captures the heteroskedasticity problem. Clustering techniques following Cameron et al. (2011) <10.1198/jbes.2010.07136> are adopted for computing cross-sectional correlation robust standard errors. The statistical tests in this package therefore accounts for potential biases arising from returns' cross-sectional correlation, autocorrelation, and volatility clustering without power loss.
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2023-06-16 |
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r-crossreg
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This package provides functions to calculate confidence intervals for crossover points of two simple linear regression lines using the non-linear regression, the delta method, the Fieller method, and the bootstrap methods.
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2023-06-16 |
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r-credule
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It provides functions to bootstrap Credit Curves from market quotes (Credit Default Swap - CDS - spreads) and price Credit Default Swaps - CDS.
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2023-06-16 |
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r-coxme
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This package fits Cox proportional hazards models containing both fixed and random effects. The random effects can have a general form, of which familial interactions (a "kinship" matrix) is a particular special case. Note that the simplest case of a mixed effects Cox model, i.e. a single random per-group intercept, is also called a "frailty" model. The approach is based on Rippatti and Palgren, Biometrics 2002.
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2023-06-16 |
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r-coxboost
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This package provides routines for fitting Cox models by likelihood based boosting for a single endpoint or in presence of competing risks
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2023-06-16 |
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r-corpora
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Utility functions for the statistical analysis of corpus frequency data. This package is a companion to the open-source course "Statistical Inference: A Gentle Introduction for Computational Linguists and Similar Creatures" ('SIGIL').
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2023-06-16 |
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r-convergenceconcepts
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This is a pedagogical package, designed to help students understanding convergence of random variables. It provides a way to investigate interactively various modes of convergence (in probability, almost surely, in law and in mean) of a sequence of i.i.d. random variables. Visualisation of simulated sample paths is possible through interactive plots. The approach is illustrated by examples and exercises through the function 'investigate', as described in Lafaye de Micheaux and Liquet (2009) <http://dx.doi.org/10.1198/tas.2009.0032>. The user can study his/her own sequences of random variables.
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2023-06-16 |
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r-conquestr
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Extends 'ACER ConQuest' by allowing R users to call 'ACER ConQuest' from within R. The user can also access 'ACER ConQuest' data objects by reading 'ACER ConQuest' System Files (generated by the 'ACER ConQuest' command 'put'). This is of particular use to those who are parsing text file output (e.g., 'show' files) as this is not consistent across releases of 'ACER ConQuest'. Requires 'ACER ConQuest' version 4.29.3 or later. A demonstration version can be downloaded from <https://shop.acer.edu.au/acer-conquest-4>.
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2023-06-16 |
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r-conjointchecks
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Implementation of a procedure (Domingue, 2012; see also Karabatsos, 2001 and Kyngdon, 2011) to test the single and double cancellation axioms of conjoint measure in data that is dichotomously coded and measured with error.
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2023-06-16 |
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r-conics
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plot conics (ellipses, hyperbolas, parabolas)
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2023-06-16 |
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r-compoissonreg
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Fit Conway-Maxwell Poisson (COM-Poisson or CMP) regression models to count data (Sellers & Shmueli, 2010) <doi:10.1214/09-AOAS306>. The package provides functions for model estimation, dispersion testing, and diagnostics. Zero-inflated CMP regression (Sellers & Raim, 2016) <doi:10.1016/j.csda.2016.01.007> is also supported.
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2023-06-16 |
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r-cvxclustr
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Alternating Minimization Algorithm (AMA) and Alternating Direction Method of Multipliers (ADMM) splitting methods for convex clustering.
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2023-06-16 |
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r-ctrdata
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Provides functions for querying, retrieving and analysing protocol- and results-related information on clinical trials from two public registers, the European Union Clinical Trials Register (EUCTR, <https://www.clinicaltrialsregister.eu/>) and ClinicalTrials.gov (CTGOV, <https://clinicaltrials.gov/>). The information is transformed and then stored in a database (mongo). Functions are provided for accessing and analysing the locally stored information on the clinical trials, as well as for identifying duplicate records. The package is motivated by the need for aggregating and trend-analysing the design, conduct and outcomes across clinical trials.
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2023-06-16 |
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r-crsnls
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Functions for nonlinear regression parameters estimation by algorithms based on Controlled Random Search algorithm. Both functions (crs4hc(), crs4hce()) adapt current search strategy by four heuristics competition. In addition, crs4hce() improves adaptability by adaptive stopping condition.
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2023-06-16 |
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r-crrstep
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Performs forward and backwards stepwise regression for the Proportional subdistribution hazards model in competing risks (Fine & Gray 1999). Procedure uses AIC, BIC and BICcr as selection criteria. BICcr has a penalty of k = log(n*), where n* is the number of primary events.
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2023-06-16 |
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r-cronr
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Create, edit, and remove 'cron' jobs on your unix-alike system. The package provides a set of easy-to-use wrappers to 'crontab'. It also provides an RStudio add-in to easily launch and schedule your scripts.
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2023-06-16 |
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r-crblocks
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Implements a statistical test for comparing bar plots or histograms of categorical data derived from a randomized block repeated measures layout.
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2023-06-16 |
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r-cranlogs
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'API' to the database of 'CRAN' package downloads from the 'RStudio' 'CRAN mirror'. The database itself is at <http://cranlogs.r-pkg.org>, see <https://github.com/r-hub/cranlogs.app> for the raw 'API'.
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2023-06-16 |
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r-cramer
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Provides R routine for the so called two-sample Cramer-Test. This nonparametric two-sample-test on equality of the underlying distributions can be applied to multivariate data as well as univariate data. It offers two possibilities to approximate the critical value both of which are included in this package.
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2023-06-16 |
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r-cpa
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The package includes functions to test and compare causal models.
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2023-06-16 |
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r-coxphmic
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Sparse estimation for Cox PH models is done via Minimum approximated Information Criterion (MIC) by Su, Wijayasinghe, Fan, and Zhang (2016) <DOI:10.1111/biom.12484>. MIC mimics the best subset selection using a penalized likelihood approach yet with no need of a tuning parameter. The problem is further reformulated with a re-parameterization step so that it reduces to one unconstrained non-convex yet smooth programming problem, which can be solved efficiently. Furthermore, the re-parameterization tactic yields an additional advantage in terms of circumventing post-selection inference.
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2023-06-16 |
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r-cubfits
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Estimating mutation and selection coefficients on synonymous codon bias usage based on models of ribosome overhead cost (ROC). Multinomial logistic regression and Markov Chain Monte Carlo are used to estimate and predict protein production rates with/without the presence of expressions and measurement errors. Work flows with examples for simulation, estimation and prediction processes are also provided with parallelization speedup. The whole framework is tested with yeast genome and gene expression data of Yassour, et al. (2009) <doi:10.1073/pnas.0812841106>.
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2023-06-16 |
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r-cqrreg
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Estimate quantile regression(QR) and composite quantile regression (cqr) and with adaptive lasso penalty using interior point (IP), majorize and minimize(MM), coordinate descent (CD), and alternating direction method of multipliers algorithms(ADMM).
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2023-06-16 |
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r-coxphw
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Implements weighted estimation in Cox regression as proposed by Schemper, Wakounig and Heinze (Statistics in Medicine, 2009, <doi:10.1002/sim.3623>) and as described in Dunkler, Ploner, Schemper and Heinze (Journal of Statistical Software, 2018, <doi:10.18637/jss.v084.i02>). Weighted Cox regression provides unbiased average hazard ratio estimates also in case of non-proportional hazards. Approximated generalized concordance probability an effect size measure for clear-cut decisions can be obtained. The package provides options to estimate time-dependent effects conveniently by including interactions of covariates with arbitrary functions of time, with or without making use of the weighting option.
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2023-06-16 |
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r-countrycode
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Standardize country names, convert them into one of eleven coding schemes, convert between coding schemes, and assign region descriptors.
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2023-06-16 |
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r-cortest
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There are 6 novel robust tests for equal correlation. They are all based on logistic regressions. U are proportion to different types of correlation in 6 methods. The ST1() is based on Pearson correlation. ST2() improved ST1() by using median absolute deviation. ST3() utilized type M correlation and ST4() used Spearman correlation. ST5() and ST6() used two different ways to combine ST3() and ST4(). We highly recommend ST5() according to the passage New Statistical Methods for Constructing Robust Differential Correlation Networks to characterize the interactions among microRNAs published in Scientific Reports.
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2023-06-16 |
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r-convertgraph
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Converts graphical file formats (SVG, PNG, JPEG, BMP, GIF, PDF, etc) to one another. The exceptions are the SVG file format that can only be converted to other formats and in contrast, PDF format, which can only be created from others graphical formats. The main purpose of the package was to provide a solution for converting SVG file format to PNG which is often needed for exporting graphical files produced by R widgets.
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2023-06-16 |
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r-conditionz
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Provides ability to control how many times in function calls conditions are thrown (shown to the user). Includes control of warnings and messages.
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2023-06-16 |
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r-bayess
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bayess contains a collection of functions that allows the reenactment of the R programs used in the book "Bayesian Essentials with R" (revision of "Bayesian Core") without further programming. R code being available as well, they can be modified by the user to conduct one's own simulations.
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2023-06-16 |
