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r-indtestpp
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Several parametric and non-parametric tests and measures to check independence between two or more (homogeneous or nonhomogeneous) point processes in time are provided. Tools for simulating point processes in one dimension with different types of dependence are also implemented.
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2025-04-22 |
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r-indirect
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Functions are provided to facilitate prior elicitation for Bayesian generalised linear models using independent conditional means priors. The package supports the elicitation of multivariate normal priors for generalised linear models. The approach can be applied to indirect elicitation for a generalised linear model that is linear in the parameters. The package is designed such that the facilitator executes functions within the R console during the elicitation session to provide graphical and numerical feedback at each design point. Various methodologies for eliciting fractiles (equivalently, percentiles or quantiles) are supported, including versions of the approach of Hosack et al. (2017) <doi:10.1016/j.ress.2017.06.011>. For example, experts may be asked to provide central credible intervals that correspond to a certain probability. Or experts may be allowed to vary the probability allocated to the central credible interval for each design point. Additionally, a median may or may not be elicited.
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2025-04-22 |
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r-indiantaxcalc
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Calculate Indian Income Tax liability for Financial years of Individual resident aged below 60 years,Senior Citizen,Super Senior Citizen, Firm, Local Authority, Any Non Resident Individual / Hindu Undivided Family / Association of Persons /Body of Individuals / Artificial Judicial Person, Co-operative Society.
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2025-04-22 |
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r-indexnumr
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Computes bilateral and multilateral index numbers. It has support for several standard bilateral indices as well as the GEKS multilateral index number methods (see Ivancic, Diewert and Fox (2011) <doi:10.1016/j.jeconom.2010.09.003>) . It also supports updating of GEKS indexes using several splicing methods.
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2025-04-22 |
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r-inbreedr
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A framework for analysing inbreeding and heterozygosity-fitness correlations (HFCs) based on microsatellite and SNP markers.
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2025-04-22 |
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r-imrmc
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Do Multi-Reader, Multi-Case (MRMC) analyses of data from imaging studies where clinicians (readers) evaluate patient images (cases). What does this mean? ... Many imaging studies are designed so that every reader reads every case in all modalities, a fully-crossed study. In this case, the data is cross-correlated, and we consider the readers and cases to be cross-correlated random effects. An MRMC analysis accounts for the variability and correlations from the readers and cases when estimating variances, confidence intervals, and p-values. The functions in this package can treat arbitrary study designs and studies with missing data, not just fully-crossed study designs. The initial package analyzes the reader-average area under the receiver operating characteristic (ROC) curve with U-statistics according to Gallas, Bandos, Samuelson, and Wagner 2009 <doi:10.1080/03610920802610084>. Additional functions analyze other endpoints with U-statistics (binary performance and score differences) following the work by Gallas, Pennello, and Myers 2007 <doi:10.1364/JOSAA.24.000B70>. Package development and documentation is at <https://github.com/DIDSR/iMRMC/tree/master>.
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2025-04-22 |
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r-imputeyn
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Method brings less bias and more efficient estimates for AFT models.
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2025-04-22 |
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r-imputer
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Multivariate Expectation-Maximization (EM) based imputation framework that offers several different algorithms. These include regularisation methods like Lasso and Ridge regression, tree-based models and dimensionality reduction methods like PCA and PLS.
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2025-04-22 |
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r-imputemissings
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Compute missing values on a training data set and impute them on a new data set. Current available options are median/mode and random forest.
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2025-04-22 |
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r-imprprobest
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A minimum distance estimator is calculated for an imprecise probability model. The imprecise probability model consists of upper coherent previsions whose credal sets are given by a finite number of constraints on the expectations. The parameter set is finite. The estimator chooses that parameter such that the empirical measure lies next to the corresponding credal set with respect to the total variation norm.
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2025-04-22 |
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r-importar
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Enables 'Python'-like importing/loading of packages or functions with aliasing to prevent namespace conflicts.
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2025-04-22 |
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r-import
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This is an alternative mechanism for importing objects from packages. The syntax allows for importing multiple objects from a package with a single command in an expressive way. The import package bridges some of the gap between using library (or require) and direct (single-object) imports. Furthermore the imported objects are not placed in the current environment. It is also possible to import objects from stand-alone .R files. For more information, refer to the package vignette.
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2025-04-22 |
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r-impimp
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Imputing blockwise missing data by imprecise imputation, featuring a domain-based, variable-wise, and case-wise strategy. Furthermore, the estimation of lower and upper bounds for unconditional and conditional probabilities based on the obtained imprecise data is implemented. Additionally, two utility functions are supplied: one to check whether variables in a data set contain set-valued observations; and another to merge two already imprecisely imputed data. The method is described in a technical report by Endres, Fink and Augustin (2018, <doi:10.5282/ubm/epub.42423>).
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2025-04-22 |
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r-impactiv
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In this package, you can find two functions proposed in Ding, Geng and Zhou (2011) to estimate direct and indirect causal effects with randomization and multiple-component intervention using instrumental variable method.
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2025-04-22 |
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r-impact
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Implement a multivariate analysis of the impact of items to identify a bias in the questionnaire validation of Likert-type scale variables. The items requires considering a null value (category doesn't have tendency). Offering frequency, importance and impact of the items.
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2025-04-22 |
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r-immailgun
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Send emails using the 'mailgun' api. To use this package you will need an account from <https://www.mailgun.com> .
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2025-04-22 |
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r-imis
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IMIS algorithm draws samples from the posterior distribution. The user has to define the following R functions in advance: prior(x) calculates prior density of x, likelihood(x) calculates the likelihood of x, and sample.prior(n) draws n samples from the prior distribution.
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2025-04-22 |
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r-imgw
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Download Polish meteorological and hydrological data from the Institute of Meteorology and Water Management - National Research Institute (<https://dane.imgw.pl/>). This package also allows for adding geographical coordinates for each observation.
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2025-04-22 |
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r-imgur
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A complete API client for the image hosting service Imgur.com, including the an imgur graphics device, enabling the easy upload and sharing of plots.
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2025-04-22 |
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r-imfdata
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Search, extract and formulate IMF's datasets.
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2025-04-22 |
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r-imap
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Zoom in and out of maps or any supplied lines or points, with control for color, poly fill, and aspect.
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2025-04-22 |
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r-imak
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This is an Automatic Item Generator for Psychological Assessment. Items created with the 'IMak' package should not be used in applied settings as part of the working protocol without ensuring first that the items meet the required psychometric quality standards (see Blum & Holling, 2018) <DOI:10.3389/fpsyg.2018.01286>.
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2025-04-22 |
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r-imageviewer
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Display a 2D-matrix data as a interactive zoomable gray-scale image viewer, providing tools for manual data inspection. The viewer window shows cursor guiding lines and a corresponding data slices for both axes at the current cursor position. A tool-bar allows adjusting image display brightness/contrast through WebGL filters and performing basic high-pass/low-pass filtering.
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2025-04-22 |
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r-ihs
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Density, distribution function, quantile function and random generation for the inverse hyperbolic sine distribution. This package also provides a function that can fit data to the inverse hyperbolic sine distribution using maximum likelihood estimation.
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2025-04-22 |
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r-ig.vancouver.2014.topcolour
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A dataset of the top colours of photos from Instagram taken in 2014 in the city of Vancouver, British Columbia, Canada. It consists of: top colour and counts data. This data was obtained using the Instagram API. Instagram is a web photo sharing service. It can be found at: <https://instagram.com>. The Instagram API is documented at: <https://instagram.com/developer/>.
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2025-04-22 |
