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r-jeek
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Provides a fast and scalable joint estimator for integrating additional knowledge in learning multiple related sparse Gaussian Graphical Models (JEEK). The JEEK algorithm can be used to fast estimate multiple related precision matrices in a large-scale. For instance, it can identify multiple gene networks from multi-context gene expression datasets. By performing data-driven network inference from high-dimensional and heterogeneous data sets, this tool can help users effectively translate aggregated data into knowledge that take the form of graphs among entities. Please run demo(jeek) to learn the basic functions provided by this package. For further details, please read the original paper: Beilun Wang, Arshdeep Sekhon, Yanjun Qi "A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models" (ICML 2018) <arXiv:1806.00548>.
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2025-04-22 |
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r-jdx
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Simplifies and extends data exchange between 'R' and 'Java'.
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2025-04-22 |
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r-jdmbs
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Black-Scholes model [Black (1973) <doi:10.1086/260062>] is important to calculate option prices in the stock market and a variety of improved models are studied. In this package, I propose methods in order to calculate both Black-Scholes model and Jump diffusion model [Kou (2002) <doi:10.1287/mnsc.48.8.1086.166>] by Monte Carlo methods. This package can be used for computational finance.
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2025-04-22 |
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r-jcp
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Procedures for joint detection of changes in both expectation and variance in univariate sequences. Performs a statistical test of the null hypothesis of the absence of change points. In case of rejection performs an algorithm for change point detection. References - Bivariate change point detection (2019+), Michael Messer.
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2025-04-22 |
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r-jaggr
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All the data and functions used to produce the book. We do not expect most people to use the package for any other reason than to get simple access to the 'JAGS' model files, the data, and perhaps run some of the simple examples. The authors of the book are David Lucy (now sadly deceased) and James Curran. It is anticipated that a manuscript will be provided to Taylor and Francis around February 2020, with bibliographic details to follow at that point. Until such time, further information can be obtained by emailing James Curran.
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2025-04-22 |
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r-jacpop
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Uses the Jaccard similarity index to account for population structure in sequencing studies. This method was specifically designed to detect population stratification based on rare variants, hence it will be especially useful in rare variant analysis.
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2025-04-22 |
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r-jaatha
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An estimation method that can use computer simulations to approximate maximum-likelihood estimates even when the likelihood function can not be evaluated directly. It can be applied whenever it is feasible to conduct many simulations, but works best when the data is approximately Poisson distributed. It was originally designed for demographic inference in evolutionary biology. It has optional support for conducting coalescent simulation using the 'coala' package.
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2025-04-22 |
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r-ivprobit
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Compute the instrumental variables probit model using the Amemiya's Generalized Least Squares estimators (Amemiya, Takeshi, (1978) <doi: 10.2307/1911443>).
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2025-04-22 |
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r-ivpanel
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Fit the instrumental panel data models: the fixed effects, random effects and between models.
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2025-04-22 |
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r-ivfixed
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Fit an Instrumental least square dummy variable model
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2025-04-22 |
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r-itunesr
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To enable 'iOS' App Developers to access iTunes App Store Ratings and Reviews using R to extract Basic App Information and Reviews submitted by their App users, Since Apple Store does not provide this straightforward.
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2025-04-22 |
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r-itsmr
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Provides functions for modeling and forecasting time series data. Forecasting is based on the innovations algorithm. A description of the innovations algorithm can be found in the textbook "Introduction to Time Series and Forecasting" by Peter J. Brockwell and Richard A. Davis. <http://www.springer.com/us/book/9781475777505>.
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2025-04-22 |
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r-itop
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Infers a topology of relationships between different datasets, such as multi-omics and phenotypic data recorded on the same samples. We based this methodology on the RV coefficient (Robert & Escoufier, 1976, <doi:10.2307/2347233>), a measure of matrix correlation, which we have extended for partial matrix correlations and binary data (Aben et al., 2018, <doi:10.1101/293993>).
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2025-04-22 |
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r-itertools2
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A port of Python's excellent itertools module to R for efficient looping.
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2025-04-22 |
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r-itertools
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Various tools for creating iterators, many patterned after functions in the Python itertools module, and others patterned after functions in the 'snow' package.
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2025-04-22 |
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r-iterpc
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Iterator for generating permutations and combinations. They can be either drawn with or without replacement, or with distinct/ non-distinct items (multiset). The generated sequences are in lexicographical order (dictionary order). The algorithms to generate permutations and combinations are memory efficient. These iterative algorithms enable users to process all sequences without putting all results in the memory at the same time. The algorithms are written in C/C++ for faster performance. Note: 'iterpc' is no longer being maintained. Users are recommended to switch to 'arrangements'.
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2025-04-22 |
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r-italy
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Provides two record linkage data sets on the Italian Survey on Household and Wealth, 2008 and 2010, a sample survey conducted by the Bank of Italy every two years. The 2010 survey covered 13,702 individuals, while the 2008 survey covered 13,734 individuals. The following categorical variables are included in this data set: year of birth, working status, employment status, branch of activity, town size, geographical area of birth, sex, whether or not Italian national, and highest educational level obtained. Unique identifiers are available to assess the accuracy of one’s method. Please see Steorts (2015) <DOI:10.1214/15-BA965SI> to find more details about the data set.
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2025-04-22 |
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r-iswr
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Data sets and scripts for text examples and exercises in P. Dalgaard (2008), `Introductory Statistics with R', 2nd ed., Springer Verlag, ISBN 978-0387790534.
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2025-04-22 |
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r-istacr
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You can access to open data published in Instituto Canario De Estadistica (ISTAC) APIs at <https://www.gobiernodecanarias.org/istac/api/>.
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2025-04-22 |
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r-isoweek
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This is an substitute for the %V and %u formats which are not implemented on Windows. In addition, the package offers functions to convert from standard calender format yyyy-mm-dd to and from ISO 8601 week format yyyy-Www-d.
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2025-04-22 |
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r-isotonic.pen
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Given a response y and a one- or two-dimensional predictor, the isotonic regression estimator is calculated with the usual orderings.
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2025-04-22 |
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r-isoplotr
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Plots U-Pb data on Wetherill and Tera-Wasserburg concordia diagrams. Calculates concordia and discordia ages. Performs linear regression of measurements with correlated errors using 'York', 'Titterington' and 'Ludwig' approaches. Generates Kernel Density Estimates (KDEs) and Cumulative Age Distributions (CADs). Produces Multidimensional Scaling (MDS) configurations and Shepard plots of multi-sample detrital datasets using the Kolmogorov-Smirnov distance as a dissimilarity measure. Calculates 40Ar/39Ar ages, isochrons, and age spectra. Computes weighted means accounting for overdispersion. Calculates U-Th-He (single grain and central) ages, logratio plots and ternary diagrams. Processes fission track data using the external detector method and LA-ICP-MS, calculates central ages and plots fission track and other data on radial (a.k.a. 'Galbraith') plots. Constructs total Pb-U, Pb-Pb, K-Ca, Re-Os, Sm-Nd, Lu-Hf, Rb-Sr and 230Th-U isochrons as well as 230Th-U evolution plots.
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2025-04-22 |
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r-isopat
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The function calculates the isotopic pattern (fine structures) for a given chemical formula.
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2025-04-22 |
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r-isoci
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Some functions for confidence intervals for current status data based on transformations and bootstrap.
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2025-04-22 |
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r-ismev
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Functions to support the computations carried out in `An Introduction to Statistical Modeling of Extreme Values' by Stuart Coles. The functions may be divided into the following groups; maxima/minima, order statistics, peaks over thresholds and point processes.
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2025-04-22 |
