Statistical software are specialized computer programs for analysis in statistics and econometrics.
A computer program is a collection of instructions that performs a specific task when executed by a computer. A computer requires programs to function.
Statistics is a branch of mathematics dealing with data collection, organization, analysis, interpretation and presentation. In applying statistics to, for example, a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model process to be studied. Populations can be diverse topics such as "all people living in a country" or "every atom composing a crystal". Statistics deals with all aspects of data, including the planning of data collection in terms of the design of surveys and experiments. See glossary of probability and statistics.
Econometrics is the application of statistical methods to economic data in order to give empirical content to economic relationships. More precisely, it is "the quantitative analysis of actual economic phenomena based on the concurrent development of theory and observation, related by appropriate methods of inference". An introductory economics textbook describes econometrics as allowing economists "to sift through mountains of data to extract simple relationships". The first known use of the term "econometrics" was by Polish economist Paweł Ciompa in 1910. Jan Tinbergen is considered by many to be one of the founding fathers of econometrics. Ragnar Frisch is credited with coining the term in the sense in which it is used today.
Programming with Big Data in R (pbdR) is a series of R packages and an environment for statistical computing with big data by using high-performance statistical computation. The pbdR uses the same programming language as R with S3/S4 classes and methods which is used among statisticians and data miners for developing statistical software. The significant difference between pbdR and R code is that pbdR mainly focuses on distributed memory systems, where data are distributed across several processors and analyzed in a batch mode, while communications between processors are based on MPI that is easily used in large high-performance computing (HPC) systems. R system mainly focuses on single multi-core machines for data analysis via an interactive mode such as GUI interface.
In computing, SPMD is a technique employed to achieve parallelism; it is a subcategory of MIMD. Tasks are split up and run simultaneously on multiple processors with different input in order to obtain results faster. SPMD is the most common style of parallel programming. It is also a prerequisite for research concepts such as active messages and distributed shared memory.
Big data is a field that treats of ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity may lead to a higher false discovery rate. Big data challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy and data source. Big data was originally associated with three key concepts: volume, variety, and velocity. Other concepts later attributed with big data are veracity and value.
Scikit-learn is a free software machine learning library for the Python programming language. It features various classification, regression and clustering algorithms including support vector machines, random forests, gradient boosting, k-means and DBSCAN, and is designed to interoperate with the Python numerical and scientific libraries NumPy and SciPy.
Statsmodels is a Python package that allows users to explore data, estimate statistical models, and perform statistical tests. An extensive list of descriptive statistics, statistical tests, plotting functions, and result statistics are available for different types of data and each estimator. It complements SciPy's stats module.
In statistics, the generalized linear model (GLM) is a flexible generalization of ordinary linear regression that allows for response variables that have error distribution models other than a normal distribution. The GLM generalizes linear regression by allowing the linear model to be related to the response variable via a link function and by allowing the magnitude of the variance of each measurement to be a function of its predicted value.
ADaMSoft is a free and open-source statistical software developed in Java and can run on any platform supporting Java.
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems. Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information from a data set and transform the information into a comprehensible structure for further use. Data mining is the analysis step of the "knowledge discovery in databases" process, or KDD. Aside from the raw analysis step, it also involves database and data management aspects, data pre-processing, model and inference considerations, interestingness metrics, complexity considerations, post-processing of discovered structures, visualization, and online updating. The difference between data analysis and data mining is that data analysis is to summarize the history such as analyzing the effectiveness of a marketing campaign, in contrast, data mining focuses on using specific machine learning and statistical models to predict the future and discover the patterns among data.
ADMB or AD Model Builder is a free and open source software suite for non-linear statistical modeling. It was created by David Fournier and now being developed by the ADMB Project, a creation of the non-profit ADMB Foundation. The "AD" in AD Model Builder refers to the automatic differentiation capabilities that come from the AUTODIF Library, a C++ language extension also created by David Fournier, which implements reverse mode automatic differentiation. A related software package, ADMB-RE, provides additional support for modeling random effects.
MaxStat is a statistical analysis software platform specifically designed for students and researchers with little background in statistics. It was developed in Germany by MaxStat Software.
MINUIT, now MINUIT2, is a numerical minimization computer program originally written in the FORTRAN programming language by CERN staff physicist Fred James in the 1970s. The program searches for minima in a user-defined function with respect to one or more parameters using several different methods as specified by the user. The original FORTRAN code was later ported to C++ by the ROOT project; both the FORTRAN and C++ versions are in use today. The program is very widely used in particle physics, and hundreds of published papers cite use of MINUIT. In the early 2000s Fred James started a project to implement MINUIT in C++ using object-oriented programming. The new MINUIT is an optional package (minuit2) in the ROOT release. As of October 2014 the latest version is 5.34.14, released on 24 January 2014. There is also a Java port as well as several Python ports.
WinBUGS is statistical software for Bayesian analysis using Markov chain Monte Carlo (MCMC) methods.
Analytica is a visual software package developed by Lumina Decision Systems for creating, analyzing and communicating quantitative decision models. As a modeling environment, it is interesting in the way it combines hierarchical influence diagrams for visual creation and view of models, intelligent arrays for working with multidimensional data, Monte Carlo simulation for analyzing risk and uncertainty, and optimization, including linear and nonlinear programming. Its design, especially its influence diagrams and treatment of uncertainty, is based on ideas from the field of decision analysis. As a computer language, it is notable in combining a declarative (non-procedural) structure for referential transparency, array abstraction, and automatic dependency maintenance for efficient sequencing of computation.
Angoss Software Corporation, headquartered in Toronto, Ontario, Canada, with offices in the United States and UK, is a provider of predictive analytics systems through software licensing and services. Angoss' customers represent industries including finance, insurance, mutual funds, retail, health sciences, telecom and technology. The company was founded in 1984, and publicly traded on the TSX Venture Exchange from 2008-2013 under the ticker symbol ANC. In June 2013 the private equity firm Peterson Partners acquired Angoss for $8.4 million.
ASReml is a statistical software package for fitting linear mixed models using restricted maximum likelihood, a technique commonly used in plant and animal breeding and quantitative genetics as well as other fields. It is notable for its ability to fit very large and complex data sets efficiently, due to its use of the average information algorithm and sparse matrix methods.
GNU Octave is software featuring a high-level programming language, primarily intended for numerical computations. Octave helps in solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with MATLAB. It may also be used as a batch-oriented language. Since it is part of the GNU Project, it is free software under the terms of the GNU General Public License.
SPSS Statistics is a software package used for interactive, or batched, statistical analysis. Long produced by SPSS Inc., it was acquired by IBM in 2009. The current versions (2015) are named IBM SPSS Statistics.
R is a programming language and free software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. The R language is widely used among statisticians and data miners for developing statistical software and data analysis. Polls, data mining surveys, and studies of scholarly literature databases show substantial increases in popularity in recent years. as of March 2019, R ranks 14th in the TIOBE index, a measure of popularity of programming languages.
gretl is an open-source statistical package, mainly for econometrics. The name is an acronym for GnuRegression, Econometrics and Time-seriesLibrary.
S-PLUS is a commercial implementation of the S programming language sold by TIBCO Software Inc.
EViews is a statistical package for Windows, used mainly for time-series oriented econometric analysis. It is developed by Quantitative Micro Software (QMS), now a part of IHS. Version 1.0 was released in March 1994, and replaced MicroTSP. The TSP software and programming language had been originally developed by Robert Hall in 1965. The current version of EViews is 10, released in June 2017.
RATS, an abbreviation of Regression Analysis of Time Series, is a statistical package for time series analysis and econometrics. RATS is developed and sold by Estima, Inc., located in Evanston, IL.
The following tables compare general and technical information for a number of statistical analysis packages.
The following tables provide a comparison of numerical-analysis software.
Kernel regression is a non-parametric technique in statistics to estimate the conditional expectation of a random variable. The objective is to find a non-linear relation between a pair of random variables X and Y.
PSPP is a free software application for analysis of sampled data, intended as a free alternative for IBM SPSS Statistics. It has a graphical user interface and conventional command-line interface. It is written in C and uses GNU Scientific Library for its mathematical routines. The name has "no official acronymic expansion".
Chronux is an open-source software package developed for the loading, visualization and analysis of a variety of modalities / formats of neurobiological time series data. Usage of this tool enables neuroscientists to perform a variety of analysis on multichannel electrophysiological data such as LFP, EEG, MEG, Neuronal spike times and also on spatiotemporal data such as FMRI and dynamic optical imaging data. The software consists of a set of MATLAB routines interfaced with C libraries that can be used to perform the tasks that constitute a typical study of neurobiological data. These include local regression and smoothing, spike sorting and spectral analysis - including multitaper spectral analysis, a powerful nonparametric method to estimate power spectrum. The package also includes some GUIs for time series visualization and analysis. Chronux is GNU GPL v2 licensed.
JASP is a free and open-source graphical program for statistical analysis, designed to be easy to use, and familiar to users of SPSS. Additionally, it provides many Bayesian statistical methods. JASP generally produces APA style results tables and plots to ease publication. It promotes open science by integration with the Open Science Framework and reproducibility by integrating the analysis settings into the results. The development of JASP is financially supported by several universities and research funds.