The JavaNumerics page provides a focal point for information on numerical computing in Java. Java Specification Request for MultiArrays under consideration. The goals of the Numerics Working Group of the Java Grande Forum are 1 to assess the suitability of Java for numerical computation, 2 to work towards community consensus on actions which can be taken to overcome deficiencies of the language and its run-time environment, and 3 to encourage the development of APIs for core mathematical operations.

## JDistlib—Java Statistical Distribution Library

The Group hosts open meetings and other forums to discuss these issues. Moreira, Samuel P. Slides in Powerpoint. Blount and S. Chatterjee January Is Java ready for computational science? Developing numerical libraries in Java Ronald F.

Boisvert, Jack J. Dongarra, Roldan Pozo, Karin A. Remington, and G. Kahan and Joseph D. Index of Scientific Java resources on the Web Mathtools. Java Community Process Sun Microsystems. Please address comments about this page to boisvert nist. Java Specification Request for Floating-Point Extensions has been withdrawn due to difficulties in setting up an expert group. Numerics Working Group. Proposed extension of java.

Numeric SciMark is a composite benchmark comprising of FFT kernels, finite-difference stencils, Monte Carlo simulations, sparse matrix computations, and direct LU factorization. Java Grande Benchmark Suite is a collection of low-level kernels, and applications for scientific and technical computing. Java Linpack Benchmark is a translation of the popular Linpack benchmark, originally written in Fortran.

It measures the performance solving a x dense linear system. Java matrix benchmark is a tool for evaluating the performance and stability of java matrix libraries. ArciMath BigDecimal is an extension of java. Colt is a free Java toolkit containing data structures and utilities intended for high performance computing.

Commons-Math The Jakarta Mathematics Library is is a library of lightweight, self-contained mathematics and statistics components addressing the most common problems not available in the Java programming language.

Drejan open-source Java library for linear and non-linear least-squares regression and regularized least-squares classification. The collection also contains extensions to java. Math and new classes for numeric output formatting. IBM's AlphaWorks contains several tools of interest, including library of correctly rounded elementary functions intended for use with Java.

Ninjaa set of classes for numerically intensive Java, including complex, multidimensional arrays, and the BLAS. Java Ultimate Math Packagea framework for arbitrary precision computations. The Java3D effort produced a matrix package for use in graphics. JScia set of Java packages for linear algebra, statistics, wavelets. It contains classes for univariate and multivariate spline approximation on scattered meshes, as well as core matrix and linear system solution classes.

Koalog Constraint Solver is a commercial Java library for solving combinatorial optimization problems using Constraint Programming or Local Search. Least Squares Software markets the jCrunch[tm] class libraries for numerical computing. The package performs multi precision floating point arithmetic with arbitrary precision level.Laurie Snell, Mathematics Dept.

A Chance course is a case study quantitative literacy course designed to make students more informed and critical readers of current news items that use probability and statistics, as reported in daily newspapers. This site contains: Chance News, a monthly newsletter with abstracts of articles from current newspapers and journals, and suggestions for discussion questions for class use, with an archive; video lectures and audio discussions of Chance topics; syllabi of previous Chance courses and articles that have been written about them; a Teacher's Guide and other materials useful for teaching a Chance course; and links to related Internet sources for teaching a probability or statistics course.

**Java Math Library**

The Chance team of developers includes: J. Grinstead and J. Laurie Snell. Math FAQ How to calculate all possible groupings of objects where order does - or doesn't - matter. Probability and Statistics - Math Forum Links to some of the best Internet resources for probability and statistics: classroom materials, software, Internet projects, and public forums for discussion.

Probability and Statistics MathPages - Kevin Brown More than 40 "informal notes" by Kevin Brown on probability and statistics: evaluating probabilities of Boolean events, area under the bell curve, N items distributed in M bins, dice rolling a given sum, a better lottery, meetings and birthdays, on random chords, and many more.

Probability Explorer - Hollylynne Stohl An open-ended learning environment for Windows for representing data in multiple ways, engaging students in designing, simulating, and analyzing results of probability experiments. The software environment can be used for activities from upper elementary grades through high school.

Data are represented in Probability Explorer with randomly generated icons that can be sorted, stacked in a pictograph or lined up in the sequence in which they occurred. A Pie Graph relative frequencyBar Graph frequencyand Data Table counts, fractions, decimals, and percents are also available to display results in static form as well as changing dynamically during a simulation.

A demo version available for download and the full version may be purchased. Probability - Math Forum, Ask Dr. Math FAQ An introduction to basic concepts. The Probability Web - Jim Pitman A collection of pages to serve people with interests in probability theory and its applications. There is also a rudimentary search engine. Originally conceived by Phil Pollett. The Problem of Points - Isaac Reed An age-old gambling problem led to the development of probability by French mathematicians Pascal and Fermat in the 17th century.

The lessons, which emphasize Includes answers and explanations. Activity Resources - Activity Resources Inc. Created by Mary Laycock for mathematics teachers, with the goal of providing a real understanding of mathematics through hands-on manipulative activities. Purchase books and manipulatives on arithmetic, base ten, red and blue blocks, Cuisenaire rods, A great time-saver if you want to show only segments of a particular video.

Videos on statistics and probability concepts. Air Pollution: A Local and Global Problem - Karen Bardeen Students investigate the problem of air pollution in a given location and research possible solutions using a variety of tools laboratory technology, Internet resources, multimedia technology, etc.

Mathematics goals include estimating, making, and Algebra in Simplest Terms - Annenberg Media In this video series for college and high school classrooms and adult learners, host Sol Garfunkel explains how algebra is used for solving real-world problems. Free sign up is required for first-time users of the online videos.

Materials videos and Read and search archived messages; and register to post to the discussions. Al Zimmermann's Programming Contests - Al Zimmermann An "arena where demented computer programmers compete for glory and for some cool prizes. Andrew M. Alexander JavaScript by Alexander includes "the gear seer," which shows not just bike gear ratios but gear inches and meters development.Current release is version 0.

October 10, Go to the project page to download the package, to report bugs, or to discuss about this project. You can browse the rudimentary Javadocif you like. Note: Thanks to MichaeL, who alerted me that v0. I have since reuploaded the binary for v0. Apologies the inconvenience.

Version 0. VectorMath Responded to bug 29 by adding an option to sort for Shapiro-Wilk test. Thank you anonymous bug reporter!

Sync with R PR Note: Since JDistlib includes bleeding edge fixes, its output may be different than that of the recently released R. Test cases for such bleeding edge fixes have been and will always be incorporated, guaranteeing its accuracy. Note also that JDistlib may still have bugs on its own. Your bug report is highly appreciated. Design philosophy: In this tutorial, I would assume that you already have some basic knowledge of statistics and Java programming. I tried to keep everything simple and intuitive so people could understand and use JDistlib quickly.

To that end, I designed the functions to be statically called.

### JDistlib—Java Statistical Distribution Library

I also recognize people's need to abstract the distributions and that is why I also allowed instantiation of each distribution class each of which extends GenericDistribution abstract class. Basic distributional features 1. In JDistlib, the call is represented by the function density which takes the following format: density x, parameter1, parameter2, Note that the list of parameters vary by distribution. For example, Normal distribution takes two parameters, mu and sigma, and Chi-square distribution takes only one, nu.

In JDistlib, the call is represented by the function cumulative which takes the following format: cumulative x, parameter1, parameter2, This is the function that you would call if you want to find the p-value for a given statistics e. Again, list of parameters vary by distibution, as above.

## What is it?

This is the function you would call if you are given a p-value and would like to know the corresponding value for that distribution. For example, for standard normal distribution i.

In JDistlib, the call is represented by the function quantile which takes the following format: quantile p, parameter1, parameter2, Using the example above, here is how you do it in JDistlib: System. Randomwhich is the function to generate random numbers according to that distribution. In JDistlib, the call is represented by the function random which takes the following format: random n, parameter1, parameter2, For each distribution, you can omit n if you need to generate only one.

The parameter random is the random number generator. Sign Rank and Wilcoxon distributions are implemented as dynamic classes since they require a storage matrix that is dependent on the supplied parameters. Dynamic calls In dynamic calls, you need to instantiate the distribution class with the parameters needed.

For example: To create a standard normal object, you would invoke new Normal 0,1. JDistlib by default will also instantiate Mersenne Twister as the random number generator if you wish to generate random numbers later.All Sites - items found, showing 51 to Buffon's Needling Ants - Ivars Peterson MathTrek The idea of estimating pi by randomly casting a needle onto an infinite plane ruled with parallel lines was first proposed by the naturalist and mathematician Georges Louis Leclerc Comte de Buffon In recent years, computer simulations have Mazel, Ed.

An Internet magazine on science and engineering, with tutorials and introductory articles on various areas of science, math, or engineering. Calculus VII - Leonid Kovalev Blog by a Syracuse University professor whose research interests range from potential theory to geometric mapping theory, particularly bi-Lipschitz maps.

Kovalev's posts, which date back to January,often include Scilab code or plots: "Generalized Captain Astounding's Nightclub - Dan Welchman A series of books set in a nightclub, the first of which discusses the practical applications of raising a number to the second, third, fourth and fifth powers.

Other topics forthcoming, including "The Probability. Card Colm - Colm Mulcahy This blog "explores mathematical card principles and effects for fun. Indices by alphabetical order, classified by mechanism and by objective including a list of children's gamesarranged by country and the types of cards. Also, commercial, solitaire, Career Information SIAM - Society for Industrial and Applied Mathematics Examples of questions addressed by applied mathematics -- whether genetic engineering, designer drugs, diesel engines, digital TV, financial markets, paper mills, electric power, insurance rates, inflation statistics, computer chips, compact disks, credit Carlo Emilio Bonferroni - Michael Dewey, University of Nottingham A brief description of Bonferroni's life and works, including Bonferroni's inequalities and his interest in algebraic means.

With bibliographies. Posts, which date back to March, and emphasize science, technology, engineering, and mathematics STEM and computer algebra systems CAShave included "Transforming inverse trig graphs"; "Birthday Includes a tutorial program for student review, Heyde; Columbia University An umbrella organization under which diverse research and educational activities in probability and its applications are focused and supported, especially at Columbia University, but with a view to local, national, and international visibility.

In addition Members, events, mailing list, links to other sites. Center for Technology and Teacher Education - Curry School of Education, University of Virginia An interdisciplinary group that develops materials to prepare teachers to use technology to enhance and extend students' learning of mathematics. The Quincunx is a device which allows a bead to drop through an array of pins stuck in a board.

The pins are equally spaced in a number of rows and when the Central Limit Theorem Applet - R.

### Gaussian.java

Todd Ogden; Dept. An "experiment" consists of rolling a certain number of dice dice are available in this applet and adding the number of spots showing. This experiment How many cereal boxes would you expect to have to buy to get all the prizes?

This lesson examines this expected value question and includes an online simulation. Discussion archives are searchable and browseable, and you may also join Chance Magazine - George P. Styan, Ed. A magazine about statistics and its use in society.

Information on recent issues and indexes; Available Data Sets, Articles, and Relevant Links; how to subscribe and submit articles. Without further information, how would you estimate the probability of such an event? Charlie's World - Buildcontent. Com A searchable database of hundreds of links to educational content. Math resources include interactive movies, slide shows, Java applets and more.Implementation of the normal gaussian distribution. Fields inherited from class org.

See RealDistribution. Methods inherited from class org. Since: 2. Parameters: mean - Mean for this distribution. Parameters: rng - Random number generator. Since: 3. Returns: the mean for this distribution. Returns: the standard deviation for this distribution. If the derivative does not exist at xthen an appropriate replacement should be returned, e. NaNor the limit inferior or limit superior of the difference quotient.

In other words, this method represents the cumulative distribution function CDF for this distribution. If x is more than 40 standard deviations from the mean, 0 or 1 is returned, as in these cases the actual value is within Double. The default implementation returns RealDistribution. Returns: the probability that a random variable with this distribution takes a value between x0 and x1excluding the lower and including the upper endpoint. You can override this method in order to use a Brent solver with an absolute accuracy different from the default.

Overrides: getSolverAbsoluteAccuracy in class AbstractRealDistribution Returns: the maximum absolute error in inverse cumulative probability estimates getNumericalMean public double getNumericalMean Use this method to get the numerical value of the mean of this distribution. For mean parameter muthe mean is mu. Returns: the mean or Double. NaN if it is not defined getNumericalVariance public double getNumericalVariance Use this method to get the numerical value of the variance of this distribution.

Returns: the variance possibly Double. This method must return the same value as inverseCumulativeProbability 0. Returns: lower bound of the support always Double. This method must return the same value as inverseCumulativeProbability 1.Unlike some of the numeric methods of class StrictMathall implementations of the equivalent functions of class Math are not defined to return the bit-for-bit same results.

This relaxation permits better-performing implementations where strict reproducibility is not required. By default many of the Math methods simply call the equivalent method in StrictMath for their implementation. Code generators are encouraged to use platform-specific native libraries or microprocessor instructions, where available, to provide higher-performance implementations of Math methods.

Such higher-performance implementations still must conform to the specification for Math. The quality of implementation specifications concern two properties, accuracy of the returned result and monotonicity of the method. Accuracy of the floating-point Math methods is measured in terms of ulpsunits in the last place.

For a given floating-point format, an ulp of a specific real number value is the distance between the two floating-point values bracketing that numerical value.

When discussing the accuracy of a method as a whole rather than at a specific argument, the number of ulps cited is for the worst-case error at any argument. If a method always has an error less than 0. A correctly rounded method is generally the best a floating-point approximation can be; however, it is impractical for many floating-point methods to be correctly rounded. Instead, for the Math class, a larger error bound of 1 or 2 ulps is allowed for certain methods.

Informally, with a 1 ulp error bound, when the exact result is a representable number, the exact result should be returned as the computed result; otherwise, either of the two floating-point values which bracket the exact result may be returned. For exact results large in magnitude, one of the endpoints of the bracket may be infinite.

Besides accuracy at individual arguments, maintaining proper relations between the method at different arguments is also important. Therefore, most methods with more than 0. Not all approximations that have 1 ulp accuracy will automatically meet the monotonicity requirements. The platform uses signed two's complement integer arithmetic with int and long primitive types. The developer should choose the primitive type to ensure that arithmetic operations consistently produce correct results, which in some cases means the operations will not overflow the range of values of the computation.

The best practice is to choose the primitive type and algorithm to avoid overflow. In cases where the size is int or long and overflow errors need to be detected, the methods addExactsubtractExactmultiplyExactand toIntExact throw an ArithmeticException when the results overflow.

For other arithmetic operations such as divide, absolute value, increment, decrement, and negation overflow occurs only with a specific minimum or maximum value and should be checked against the minimum or maximum as appropriate.

Since: JDK1. If the argument is zero, then the result is a zero with the same sign as the argument.GitHub is home to over 40 million developers working together to host and review code, manage projects, and build software together. If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again.

If nothing happens, download the GitHub extension for Visual Studio and try again. Imagine working in a system with a collection of contacts and wanting to match and categorize contacts with similar names, addresses or other attributes. The Fuzzy Match matching algorithm can help you do this. The Fuzzy Match algorithm can even help you find duplicate contacts, or prevent your system from adding duplicates.

This library can act on any domain object, like contact, and find similarity for various use cases. It dives deep into each character and finds out the probability that 2 or more objects are similar.

The contacts "Steven Wilson" living at "45th Avenue 5th st. It's easy for humans to ignore the small variance in spelling in names, or ignore abbreviation used in address. But for a computer program they are not the same. The string Steven does not equals Stephen and neither does Street equals st.

If our trusted computers can start looking at each character and the sequence in which they appear, it might look similar. Fuzzy matching algorithms is all about providing this level of magnification to our myopic machines. This algorithm accepts data in a list of entities called Document like a contact entity in your systemwhich can contain 1 or more Element like names, address, emails, etc. Internally each element is further broken down into 1 or more Token which are then matched using configurable MatchType.

This combination to tokenize the data and then to match them can extract similarity in a wide variety of data types. With a simple tokenization process each word here can be considered a token, and if another element has the same word they are scored on the number of matching tokens. In this example the words Wayne and Grace match 2 words out of 3 total in each elements. A scoring mechanism will match them with a result of 0.

Here we do not just look at each word, but encode it using Soundex which gives a unique code for the phonetic spelling of the name.

In cases where breaking down the Elements in words is not feasible, we split it using NGrams.

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