Paul Gilbert

Paul Gilbert

25 packages on CRAN

numDeriv

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Methods for calculating (usually) accurate numerical first and second order derivatives. Accurate calculations are done using 'Richardson''s' extrapolation or, when applicable, a complex step derivative is available. A simple difference method is also provided. Simple difference is (usually) less accurate but is much quicker than 'Richardson''s' extrapolation and provides a useful cross-check. Methods are provided for real scalar and vector valued functions.

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Gradient Projection Algorithm Rotation for Factor Analysis. See ?GPArotation.Intro for more details.

setRNG

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SetRNG provides utilities to help set and record the setting of the seed and the uniform and normal generators used when a random experiment is run. The utilities can be used in other functions that do random experiments to simplify recording and/or setting all the necessary information for reproducibility. See the vignette and reference manual for examples.

BB

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Barzilai-Borwein spectral methods for solving nonlinear system of equations, and for optimizing nonlinear objective functions subject to simple constraints. A tutorial style introduction to this package is available in a vignette on the CRAN download page or, when the package is loaded in an R session, with vignette("BB").

tfplot

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Utilities for simple manipulation and quick plotting of time series data. These utilities use the tframe package which provides a programming kernel for time series. Extensions to tframe provided in tframePlus can also be used. See the Guide vignette for examples.

EvalEst

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Provides functions for evaluating (time series) model estimation methods. These facilitate Monte Carlo experiments of repeated simulations and estimations. Also provides methods for looking at the distribution of the results from these experiments, including model roots (which are an equivalence class invariant).

tsfa

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Extraction of Factors from Multivariate Time Series. See ?00tsfa-Intro for more details.

TSdbi

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Provides a common interface to time series databases. The objective is to define a standard interface so users can retrieve time series data from various sources with a simple, common, set of commands, and so programs can be written to be portable with respect to the data source. The SQL implementations also provide a database table design, so users needing to set up a time series database have a reasonably complete way to do this easily. The interface provides for a variety of options with respect to the representation of time series in R. The interface, and the SQL implementations, also handle vintages of time series data (sometime called editions or real-time data). There is also a (not yet well tested) mechanism to handle multilingual data documentation. Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

CDNmoney

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Components of Canadian Credit Aggregates and Monetary Aggregates with continuity adjustments.

TSdata

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Illustrates the various 'TSdbi' packages with a vignette using time series data from several sources. The vignette also illustrates some simple time series manipulation and plotting using packages 'tframe' and 'tfplot'.

TSsql

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Standard SQL query functions used by SQL plugins packages for the 'TSdbi' interface to time series databases. It will mainly be used by other packages rather than directly by end users. The one exception is the function 'TSquery' which can be used to construct a time series from a database containing observations over time (e.g. balance statements for multiple years), but where the database is not specifically designed to store time series (as with other 'TSdbi' SQL plugin packages). Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

tframePlus

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Extensions and additional 'tframe' utilities.

TSmisc

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Methods to retrieve data from several different sources. This include historical quote data from 'Yahoo' and 'Oanda', economic data from 'FRED', and 'xls' and 'csv' data from different sources. Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

TSfame

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A 'fame' interface for 'TSdbi'. Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

TSsdmx

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Methods to retrieve data in the Statistical Data and Metadata Exchange ('SDMX') format from several database. (For example, 'EuroStat', the European Central Bank, the Organisation for Economic Co-operation and Development, the 'Unesco' Institute for Statistics, and the International Labor Organization.) This is a wrapper for package 'RJSDMX'. Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

TSSQLite

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An 'SQLite' interface for 'TSdbi'. Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

TSMySQL

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A 'MySQL' interface for 'TSdbi'. Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

A 'PostgreSQL' interface for 'TSdbi'. Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

TScompare

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Utilities for comparing the equality of series on two databases. Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

TSodbc

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An ODBC interface for 'TSdbi'. Comprehensive examples of all the 'TS*' packages is provided in the vignette Guide.pdf with the 'TSdata' package.

findpython

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Package designed to find an acceptable python binary.

tframe

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Functions for writing code that is independent of the representation of time.

dse

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CRTgeeDR

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Implements a semi-parametric GEE estimator accounting for missing data with Inverse-probability weighting (IPW) and for imbalance in covariates with augmentation (AUG). The estimator IPW-AUG-GEE is Doubly robust (DR).

numOSL

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Package for optimizing regular numeric problems in optically stimulated luminescence dating, such as: equivalent dose calculation, dose rate determination, growth curve fitting, decay curve decomposition, statistical age model optimization, and statistical plot visualization.