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r-cvauc
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This package contains various tools for working with and evaluating cross-validated area under the ROC curve (AUC) estimators. The primary functions of the package are ci.cvAUC and ci.pooled.cvAUC, which report cross-validated AUC and compute confidence intervals for cross-validated AUC estimates based on influence curves for i.i.d. and pooled repeated measures data, respectively. One benefit to using influence curve based confidence intervals is that they require much less computation time than bootstrapping methods. The utility functions, AUC and cvAUC, are simple wrappers for functions from the ROCR package.
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2023-06-16 |
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r-davies
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Various utilities for the Davies distribution.
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2023-06-16 |
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r-decide
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Calculates various estimates for measures of educational differentials, the relative importance of primary and secondary effects in the creation of such differentials and compares the estimates obtained from two datasets.
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2023-06-16 |
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r-deadband
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Statistical deadband algorithms are based on the Send-On-Delta concept as in Miskowicz(2006,<doi:10.3390/s6010049>). A collection of functions compare effectiveness and fidelity of sampled signals using statistical deadband algorithms.
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2023-06-16 |
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r-dcv
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This package performs several conventional Cross-validation statistical methods for climate-growth model in the climate reconstruction from tree rings, including Sign Test statistic, Reduction of Error statistic, Product Mean Test, Durbin-Watson statistic etc. This package is at its primary stage, the functions have not been tested exhaustively and more functions would be added in the comming days.
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2023-06-16 |
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r-dbx
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Provides select, insert, update, upsert, and delete database operations. Supports 'PostgreSQL', 'MySQL', 'SQLite', and more, and plays nicely with the 'DBI' package.
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2023-06-16 |
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r-datr
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Interface with the 'Dat' p2p network protocol <https://datproject.org>. Clone archives from the network, share your own files, and install packages from the network.
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2023-06-16 |
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r-deamer
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deamer provides deconvolution algorithms for the non-parametric estimation of the density f of an error-prone variable x with additive noise e. The model is y = x + e where the noisy variable y is observed, while x is unobserved. Estimation may be performed for i) a known density of the error ii) with an auxiliary sample of pure noise and iii) with an auxiliary sample of replicate (repeated) measurements. Estimation is performed using adaptive model selection and penalized contrasts.
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2023-06-16 |
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r-datetime
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Provides methods for working with nominal dates, times, and durations. Base R has sophisticated facilities for handling time, but these can give unexpected results if, for example, timezone is not handled properly. This package provides a more casual approach to support cases which do not require rigorous treatment. It systematically deconstructs the concepts origin and timezone, and de-emphasizes the display of seconds. It also converts among nominal durations such as seconds, hours, days, and weeks. See '?datetime' and '?duration' for examples. Adapted from 'metrumrg' <http://r-forge.r-project.org/R/?group_id=1215>.
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2023-06-16 |
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r-dataclean
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Includes functions that researchers or practitioners may use to clean raw data, transferring html, xlsx, txt data file into other formats. And it also can be used to manipulate text variables, extract numeric variables from text variables and other variable cleaning processes. It is originated from a author's project which focuses on creative performance in online education environment. The resulting paper of that study will be published soon.
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2023-06-16 |
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r-dams
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The single largest source of dams in the United States is the National Inventory of Dams (NID) <http://nid.usace.army.mil> from the US Army Corps of Engineers. Entire data from the NID cannot be obtained all at once and NID's website limits extraction of more than a couple of thousand records at a time. Moreover, selected data from the NID's user interface cannot not be saved to a file. In order to make the analysis of this data easier, all the data from NID was extracted manually. Subsequently, the raw data was checked for potential errors and cleaned. This package provides sample cleaned data from the NID and provides functionality to access the entire cleaned NID data.
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2023-06-16 |
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r-cwhmisc
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Miscellaneous useful or interesting functions.
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2023-06-16 |
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r-cutpointsoehr
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Use optimal equal-HR method to determine two optimal cutpoints of a continuous predictor that has a U-shaped relationship with survival outcomes based on Cox regression model. The optimal equal-HR method estimates two optimal cut-points that have approximately the same log hazard value based on Cox regression model and divides individuals into different groups according to their HR values.
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2023-06-16 |
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r-decision
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Contains a function called dmur() which accepts four parameters like possible values, probabilities of the values, selling cost and preparation cost. The dmur() function generates various numeric decision parameters like MEMV (Maximum (optimum) expected monitory value), best choice, EPPI (Expected profit with perfect information), EVPI (Expected value of the perfect information), EOL (Expected opportunity loss), which facilitate effective decision-making.
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2023-06-16 |
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r-ddm
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A set of three two-census methods to the estimate the degree of death registration coverage for a population. Implemented methods include the Generalized Growth Balance method (GGB), the Synthetic Extinct Generation method (SEG), and a hybrid of the two, GGB-SEG. Each method offers automatic estimation, but users may also specify exact parameters or use a graphical interface to guess parameters in the traditional way if desired.
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2023-06-16 |
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r-dcl
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Statistical modelling and forecasting in claims reserving in non-life insurance under the Double Chain Ladder framework by Martinez-Miranda, Nielsen and Verrall (2012).
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2023-06-16 |
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r-daag
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Various data sets used in examples and exercises in the book Maindonald, J.H. and Braun, W.J. (2003, 2007, 2010) "Data Analysis and Graphics Using R".
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2023-06-16 |
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r-d3network
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This packages is intended to make it easy to create D3 JavaScript network, tree, dendrogram, and Sankey graphs from R using data frames. !!! NOTE: Active development has moved to the networkD3 package. !!!
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2023-06-16 |
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r-currentsurvival
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The currentSurvival package contains functions for the estimation of the current cumulative incidence (CCI) and the current leukaemia-free survival (CLFS). The CCI is the probability that a patient is alive and in any disease remission (e.g. complete cytogenetic remission in chronic myeloid leukaemia) after initiating his or her therapy (e.g. tyrosine kinase therapy for chronic myeloid leukaemia). The CLFS is the probability that a patient is alive and in any disease remission after achieving the first disease remission.
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2023-06-16 |
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r-dbstats
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Prediction methods where explanatory information is coded as a matrix of distances between individuals. Distances can either be directly input as a distances matrix, a squared distances matrix, an inner-products matrix or computed from observed predictors.
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2023-06-16 |
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r-dataverse
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Provides access to Dataverse version 4 APIs <https://dataverse.org/>, enabling data search, retrieval, and deposit. For Dataverse versions <= 4.0, use the deprecated 'dvn' package <https://cran.r-project.org/package=dvn>.
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2023-06-16 |
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r-dark
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The recovery of visual sensitivity in a dark environment is known as dark adaptation. In a clinical or research setting the recovery is typically measured after a dazzling flash of light and can be described by the Mahroo, Lamb and Pugh (MLP) model of dark adaptation. The functions in this package take dark adaptation data and use nonlinear regression to find the parameters of the model that 'best' describe the data. They do this by firstly, generating rapid initial objective estimates of data adaptation parameters, then a multi-start algorithm is used to reduce the possibility of a local minimum. There is also a bootstrap method to calculate parameter confidence intervals. The functions rely upon a 'dark' list or object. This object is created as the first step in the workflow and parts of the object are updated as it is processed.
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2023-06-16 |
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r-dapr
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An easy-to-use, dependency-free set of functions for iterating over elements of various input objects. Functions are wrappers around base apply()/lapply()/vapply() functions but designed to have similar functionality to the mapping functions in the 'purrr' package <https://purrr.tidyverse.org/>. Specifically, function names more explicitly communicate the expected class of the output and functions also allow for the convenient shortcut of '~ .x' instead of the more verbose 'function(.x) .x'.
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2023-06-16 |
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r-dalex2
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Machine Learning models are widely used and have various applications in classification or regression tasks. Due to increasing computational power, availability of new data sources and new methods, ML models are more and more complex. Models created with techniques like boosting, bagging of neural networks are true black boxes. It is hard to trace the link between input variables and model outcomes. They are used because of high performance, but lack of interpretability is one of their weakest sides. In many applications we need to know, understand or prove how input variables are used in the model and what impact do they have on final model prediction. DALEX2 is a collection of tools that help to understand how complex predictive models are working. DALEX2 is a part of DrWhy universe for tools for Explanation, Exploration and Visualisation for Predictive Models.
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2023-06-16 |
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r-cvtuningcov
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This is a package for selecting tuning parameters based on cross-validation (CV) in regularized estimators of large covariance matrices. Four regularized methods are implemented: banding, tapering, hard-thresholding and soft-thresholding. Two types of matrix norms are applied: Frobenius norm and operator norm. Two types of CV are considered: K-fold CV and random CV. Usually K-fold CV use K-1 folds to train a model and the rest one fold to validate the model. The reverse version trains a model with 1 fold and validates with the rest with K-1 folds. Random CV randomly splits the data set to two parts, a training set and a validation set with user-specified sizes.
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2023-06-16 |
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r-cvd
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Methods for color vision deficiencies (CVD), to help understanding and mitigating issues with CVDs and to generate tests for diagnosis and interpretation.
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2023-06-16 |
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r-beginr
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Useful functions for R beginners, including hints for the arguments of the 'plot()' function, self-defined functions for error bars, user-customized pair plots and hist plots, enhanced linear regression figures, etc.. This package could be helpful to R experts as well.
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2023-06-16 |
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r-decode
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Integrated differential expression (DE) and differential co-expression (DC) analysis on gene expression data based on DECODE (DifferEntial CO-expression and Differential Expression) algorithm.
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2023-06-16 |
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r-cvequality
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Contains functions for testing for significant differences between multiple coefficients of variation. Includes Feltz and Miller's (1996) <DOI:10.1002/(SICI)1097-0258(19960330)15:6%3C647::AID-SIM184%3E3.0.CO;2-P> asymptotic test and Krishnamoorthy and Lee's (2014) <DOI:10.1007/s00180-013-0445-2> modified signed-likelihood ratio test. See the vignette for more, including full details of citations.
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2023-06-16 |
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r-cvcalibration
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Statistical inferences for estimating the calibration equation with error-in observations
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2023-06-16 |
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r-curvecomp
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Performs multiple comparison procedures on curve observations among different treatment groups. The methods are applicable in a variety of situations (such as independent groups with equal or unequal sample sizes, or repeated measures) by using parametric bootstrap. References to these procedures can be found at Konietschke, Gel, and Brunner (2014) <doi:10.1090/conm/622/12431> and Westfall (2011) <doi:10.1080/10543406.2011.607751>.
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2023-06-16 |
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r-dang
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A collection of utility functions.
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2023-06-16 |
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r-crisp
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Implements convex regression with interpretable sharp partitions (CRISP), which considers the problem of predicting an outcome variable on the basis of two covariates, using an interpretable yet non-additive model. CRISP partitions the covariate space into blocks in a data-adaptive way, and fits a mean model within each block. Unlike other partitioning methods, CRISP is fit using a non-greedy approach by solving a convex optimization problem, resulting in low-variance fits. More details are provided in Petersen, A., Simon, N., and Witten, D. (2016). Convex Regression with Interpretable Sharp Partitions. Journal of Machine Learning Research, 17(94): 1-31 <http://jmlr.org/papers/volume17/15-344/15-344.pdf>.
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2023-06-16 |
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r-assocafc
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When doing association analysis one does not always have the genotypes for the control population. In such cases it may be necessary to fall back on frequency based tests using well known sources for the frequencies in the control population, for instance, from the 1000 Genomes Project. The Allele Frequency Comparison ('AssocAFC') package performs multiple rare variant association analyses in both population and family-based GWAS (Genome-Wide Association Study) designs. It includes three score tests that are based on the difference of the sum of allele frequencies between cases and controls. Two of these tests, Wcorrected() and Wqls(), are collapsing-based tests and suffer from having protective and risk variants. The third test, afcSKAT(), is a score test that overcomes the mix of SNP (Single-Nucleotide Polymorphism) effect directions. For more details see Saad M and Wijsman EM (2017) <doi:10.1093/bib/bbx107>.
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2023-06-16 |
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r-csvread
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Functions for loading large (10M+ lines) CSV and other delimited files, similar to read.csv, but typically faster and using less memory than the standard R loader. While not entirely general, it covers many common use cases when the types of columns in the CSV file are known in advance. In addition, the package provides a class 'int64', which represents 64-bit integers exactly when reading from a file. The latter is useful when working with 64-bit integer identifiers exported from databases. The CSV file loader supports common column types including 'integer', 'double', 'string', and 'int64', leaving further type transformations to the user.
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2023-06-16 |
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r-corbin
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We design algorithms with linear time complexity with respect to the dimension for three commonly studied correlation structures, including exchangeable, decaying-product and K-dependent correlation structures, and extend the algorithms to generate binary data of general non-negative correlation matrices with quadratic time complexity. Jiang, W., Song, S., Hou, L. and Zhao, H. "CorBin: An efficient R package to generate high-dimensional binary data with correlation structures." Submitted to Journal of Statistical Software.
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2023-06-16 |
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r-confinterpret
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Produces descriptive interpretations of confidence intervals. Includes (extensible) support for various test types, specified as sets of interpretations dependent on where the lower and upper confidence limits sit. Provides plotting functions for graphical display of interpretations.
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2023-06-16 |
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r-compquadform
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Computes the distribution function of quadratic forms in normal variables using Imhof's method, Davies's algorithm, Farebrother's algorithm or Liu et al.'s algorithm.
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2023-06-16 |
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r-compare
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Functions to compare a model object to a comparison object. If the objects are not identical, the functions can be instructed to explore various modifications of the objects (e.g., sorting rows, dropping names) to see if the modified versions are identical.
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2023-06-16 |
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r-comp2roc
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Comparison of two ROC curves through the methodology proposed by Ana C. Braga.
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2023-06-16 |
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r-dcurver
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A Davidian curve defines a seminonparametric density, whose shape and flexibility can be tuned by easy to estimate parameters. Since a special case of a Davidian curve is the standard normal density, Davidian curves can be used for relaxing normality assumption in statistical applications (Zhang & Davidian, 2001) <doi:10.1111/j.0006-341X.2001.00795.x>. This package provides the density function, the gradient of the loglikelihood and a random generator for Davidian curves.
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2023-06-16 |
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r-dblcens
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Use EM algorithm to compute the NPMLE of CDF and also the two censoring distributions. For doubly censored data (as described in Chang and Yang (1987) Ann. Stat. 1536-47). You can also specify a constraint, it will return the constrained NPMLE and the -2 log empirical likelihood ratio. This can be used to test the hypothesis about the constraint and find confidence intervals for probability or quantile via empirical likelihood ratio theorem. Influence function of hat F may also be calculated (but may be slow).
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2023-06-16 |
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r-crn
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The crn package provides the core functions required to download and format data from the Climate Reference Network. Both daily and hourly data are downloaded from the ftp, a consolidated file of all stations is created, station metadata is extracted. In addition functions for selecting individual variables and creating R friendly datasets for them is provided.
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2023-06-16 |
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r-crantastic
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Various R tools for http://crantastic.org/
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2023-06-16 |
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r-cpgfilter
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Filter CpGs based on Intra-class Correlation Coefficients (ICCs) when replicates are available. ICCs are calculated by fitting linear mixed effects models to all samples including the un-replicated samples. Including the large number of un-replicated samples improves ICC estimates dramatically. The method accommodates any replicate design.
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2023-06-16 |
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r-coxphlb
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Performs analysis of right-censored length-biased data using Cox model. It contains model fitting and checking, and the stationarity assumption test. The model fitting and checking methods are described in Qin and Shen (2010) <doi:10.1111/j.1541-0420.2009.01287.x> and Lee, Ning, and Shen (2018) <doi:10.1007/s10985-018-9422-y>.
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2023-06-16 |
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r-cubature
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R wrappers around the cubature C library of Steven G. Johnson for adaptive multivariate integration over hypercubes and the Cuba C library of Thomas Hahn for deterministic and Monte Carlo integration. Scalar and vector interfaces for cubature and Cuba routines are provided; the vector interfaces are highly recommended as demonstrated in the package vignette.
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2023-06-16 |
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r-bbl
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Supervised learning using Boltzmann Bayes model inference, which extends naive Bayes model to include interactions. Enables classification of data into multiple response groups based on a large number of discrete predictors that can take factor values of heterogeneous levels. Either pseudo-likelihood and mean field inference can be used with L2 regularization, cross-validation, and prediction on new data. Woo et al. (2016) <doi:10.1186/s12864-016-2871-3>.
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2023-06-16 |
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r-cotrend
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Implements cointegration/cotrending rank selection algorithm in Guo and Shintani (2013) "Consistant cotrending rank selection when both stochastic and nonlinear deterministic trends are present". The Econometrics Journal 16: 473-483 <doi:10.1111/j.1368-423X.2012.00392.x>. Numbered examples correspond to Feb 2011 preprint <http://www.fas.nus.edu.sg/ecs/events/seminar/seminar-papers/05Apr11.pdf>.
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2023-06-16 |
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r-cost
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Parameter estimation, one-step ahead forecast and new location prediction methods for spatio-temporal data.
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2023-06-16 |
