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r-bayfoxr
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A Bayesian, global planktic foraminifera core top calibration to modern sea-surface temperatures. Includes four calibration models, considering species-specific calibration parameters and seasonality.
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2025-04-22 |
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r-bayesvalidate
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BayesValidate implements the software validation method described in the paper "Validation of Software for Bayesian Models using Posterior Quantiles" (Cook, Gelman, and Rubin, 2005). It inputs a function to perform Bayesian inference as well as functions to generate data from the Bayesian model being fit, and repeatedly generates and analyzes data to check that the Bayesian inference program works properly.
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2025-04-22 |
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r-bayestreeprior
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Provides a way to simulate from the prior distribution of Bayesian trees by Chipman et al. (1998) <DOI:10.2307/2669832>. The prior distribution of Bayesian trees is highly dependent on the design matrix X, therefore using the suggested hyperparameters by Chipman et al. (1998) <DOI:10.2307/2669832> is not recommended and could lead to unexpected prior distribution. This work is part of my master thesis (expected 2016).
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2025-04-22 |
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r-bayest
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Provides an Markov-Chain-Monte-Carlo algorithm for Bayesian t-tests on the effect size. The underlying Gibbs sampler is based on a two-component Gaussian mixture and approximates the posterior distributions of the effect size, the difference of means and difference of standard deviations. A posterior analysis of the effect size via the region of practical equivalence is provided, too. For more details about the Gibbs sampler see Kelter (2019) <arXiv:1906.07524>.
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2025-04-22 |
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r-bayespiecewiseicar
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Fits a piecewise exponential hazard to survival data using a Hierarchical Bayesian model with an Intrinsic Conditional Autoregressive formulation for the spatial dependency in the hazard rates for each piece. This function uses Metropolis- Hastings-Green MCMC to allow the number of split points to vary. This function outputs graphics that display the histogram of the number of split points and the trace plots of the hierarchical parameters. The function outputs a list that contains the posterior samples for the number of split points, the location of the split points, and the log hazard rates corresponding to these splits. Additionally, this outputs the posterior samples of the two hierarchical parameters, Mu and Sigma^2.
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2025-04-22 |
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r-bayespiecehazselect
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Fits a piecewise exponential hazard to survival data using a Hierarchical Bayesian model with an Intrinsic Conditional Autoregressive formulation for the spatial dependency in the hazard rates for each piece. This function uses Metropolis- Hastings-Green MCMC to allow the number of split points to vary and also uses Stochastic Search Variable Selection to determine what covariates drive the risk of the event. This function outputs trace plots depicting the number of split points in the hazard and the number of variables included in the hazard. The function saves all posterior quantities to the desired path.
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2025-04-22 |
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r-bayesni
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A Bayesian testing procedure for noninferiority trials with binary endpoints. The prior is constructed based on Bernstein polynomials with options for both informative and non-informative prior. The critical value of the test statistic (Bayes factor) is determined by minimizing total weighted error (TWE) criteria
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2025-04-22 |
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r-bayesmams
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Calculating Bayesian sample sizes for multi-arm trials where several experimental treatments are compared to a common control, perhaps even at multiple stages.
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2025-04-22 |
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r-aws.translate
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A client for 'AWS Translate' <https://aws.amazon.com/documentation/translate>, a machine translation service that will convert a text input in one language into a text output in another language.
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2025-04-22 |
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r-aws.transcribe
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Client for 'AWS Transcribe' <https://aws.amazon.com/documentation/transcribe>, a cloud transcription service that can convert an audio media file in English and other languages into a text transcript.
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2025-04-22 |
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r-aws.sqs
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A simple client package for the Amazon Web Services ('AWS') Simple Queue Service ('SQS') <https://aws.amazon.com/sqs/> 'API'.
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2025-04-22 |
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r-aws.sns
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A simple client package for the Amazon Web Services ('AWS') Simple Notification Service ('SNS') 'API' <https://aws.amazon.com/sns/>.
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2025-04-22 |
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r-aws.ses
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A simple client package for the Amazon Web Services (AWS) Simple Email Service (SES) <http://aws.amazon.com/ses/> REST API.
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2025-04-22 |
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r-aws.s3
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A simple client package for the Amazon Web Services ('AWS') Simple Storage Service ('S3') 'REST' 'API' <https://aws.amazon.com/s3/>.
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2025-04-22 |
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r-aws.lambda
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A simple client package for the Amazon Web Services ('AWS') Lambda 'API' <https://aws.amazon.com/lambda/>.
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2025-04-22 |
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r-aws.kms
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Client package for the 'AWS Key Management Service' <https://aws.amazon.com/kms/>, a cloud service for managing encryption keys.
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2025-04-22 |
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r-aws.iam
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A simple client for the Amazon Web Services ('AWS') Identity and Access Management ('IAM') 'API' <https://aws.amazon.com/iam/>.
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2025-04-22 |
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r-aws.comprehend
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Client for 'AWS Comprehend' <https://aws.amazon.com/comprehend>, a cloud natural language processing service that can perform a number of quantitative text analyses, including language detection, sentiment analysis, and feature extraction.
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2025-04-22 |
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r-awr.kms
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Encrypt plain text and 'decrypt' cipher text using encryption keys hosted at Amazon Web Services ('AWS') Key Management Service ('KMS'), on which see <https://aws.amazon.com/kms> for more information.
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2025-04-22 |
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r-assertive.types
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A set of predicates and assertions for checking the types of variables. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2025-04-22 |
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r-assertive.files
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A set of predicates and assertions for checking the properties of files and connections. This is mainly for use by other package developers who want to include run-time testing features in their own packages. End-users will usually want to use assertive directly.
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2025-04-22 |
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r-biasedurn
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Statistical models of biased sampling in the form of univariate and multivariate noncentral hypergeometric distributions, including Wallenius' noncentral hypergeometric distribution and Fisher's noncentral hypergeometric distribution (also called extended hypergeometric distribution). See vignette("UrnTheory") for explanation of these distributions.
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2025-04-22 |
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r-bhsbvar
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Provides a function for estimating the parameters of Structural Bayesian Vector Autoregression models with the method developed by Baumeister and Hamilton (2015) <doi:10.3982/ECTA12356>, Baumeister and Hamilton (2017) <doi:10.3386/w24167>, and Baumeister and Hamilton (2018) <doi:10.1016/j.jmoneco.2018.06.005>. Functions for plotting impulse responses, historical decompositions, and posterior distributions of model parameters are also provided.
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2025-04-22 |
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r-bfp
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Implements the Bayesian paradigm for fractional polynomial models under the assumption of normally distributed error terms, see Sabanes Bove, D. and Held, L. (2011) <doi:10.1007/s11222-010-9170-7>.
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2025-04-22 |
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r-bfa
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Provides model fitting for several Bayesian factor models including Gaussian, ordinal probit, mixed and semiparametric Gaussian copula factor models under a range of priors.
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2025-04-22 |
