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Polynomial Regression PHP class

A PHP regression class. Linear Regression with Forced Intercept. Not all data sets can be accurately modeled with polynomial regression regardless of the degree polynomial selected. It helps to have an understanding of the origin of the data and the function attempting to be modeled. Polynomials are one method of curve fitting. Some other methods are implemented with the Gauss-Newton class. The non-linear functions implemented are:. These classes are in beta. The key to weighting is to register a weighti...

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Polynomial Regression PHP class | polynomialregression.drque.net Reviews
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A PHP regression class. Linear Regression with Forced Intercept. Not all data sets can be accurately modeled with polynomial regression regardless of the degree polynomial selected. It helps to have an understanding of the origin of the data and the function attempting to be modeled. Polynomials are one method of curve fitting. Some other methods are implemented with the Gauss-Newton class. The non-linear functions implemented are:. These classes are in beta. The key to weighting is to register a weighti...
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1 polynomial regression
2 introduction
3 navigation
4 download
5 documentation
6 examples
7 linear regression
8 3rd degree polynomial
9 calculating r squared
10 forced coefficients
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Polynomial Regression PHP class | polynomialregression.drque.net Reviews

https://polynomialregression.drque.net

A PHP regression class. Linear Regression with Forced Intercept. Not all data sets can be accurately modeled with polynomial regression regardless of the degree polynomial selected. It helps to have an understanding of the origin of the data and the function attempting to be modeled. Polynomials are one method of curve fitting. Some other methods are implemented with the Gauss-Newton class. The non-linear functions implemented are:. These classes are in beta. The key to weighting is to register a weighti...

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polynomialregression.drque.net polynomialregression.drque.net
1

API Documentation

http://polynomialregression.drque.net/Doc/classes/ExponentiationWeighting.html

160;Class hierarchy diagram. This class will weight the terms for the regression by raising the index of the term to a given power. When the power term is positive this means those indices at the end will command more of the outcome than those at the beginning. The reverse is true for negative powers. A power of 0 has no effect and all terms are weighted equally. No public properties found. No protected methods found. No protected properties found. No private methods found. No private properties found.

2

API Documentation

http://polynomialregression.drque.net/Doc/classes/UniqueWeighting.html

160;Class hierarchy diagram. This class will weight regression input on a term-by-term basis. Typically this would be done using a table of weighting terms with one term for each data point. Regression = new PolynomialRegression( $numberOfCoefficients ); $weighting = new UniqueWeighting(); / . foreach ( $data as $dataPoint ) { $weighting- setWeight( $dataPoint[ "weight" ] ); $regression- addData( $dataPoint[ "x" ], $dataPoint[ "y" ] ); }. No public properties found. No protected methods found.

3

API Documentation

http://polynomialregression.drque.net/Doc/classes/LinearWeighting.html

160;Class hierarchy diagram. This class will weight the terms in a linear manner. The slope can be positive or negative thereby placing more emphasis on the last/first terms respectively. A slope of 0 has no effect and all terms are weighted equally. NOTE: Does not use BC math which should not be a problem. No public properties found. No protected methods found. No protected properties found. No private methods found. No private properties found. Http:/ opensource.org/licenses/gpl-license.php.

4

API Documentation

http://polynomialregression.drque.net/Doc/index.html

160;Class hierarchy diagram. Interface for weighting the regression. Implementations of this interface can be used to apply a custom weighting value that emphasizes some values more than others. Used for calculating least-square coefficients for data conforming to the function: y = a * exp( b * x ). Used for calculating least-square coefficients for data conforming to the function: Typical form: y = a * ln x b Expanded form: y = c 0 c 1 ln x c 2 ln 2 x . This class will weight regression input on a term-...

5

API Documentation

http://polynomialregression.drque.net/Doc/classes/PowRegression.html

160;Class hierarchy diagram. Used for calculating least-square coefficients for data conforming to the function: y = a * exp( b * x ). Note: Although this function overloads the polynomial regression class, the log and exponential function are not done using BC math and therefor do not have the accuracy. Regression = new PowRegression(); / . $regression- addData( $x, $y ); / . $coefficients = $regression- getCoefficients(); / . $y = $regression- interpolate( $coefficients, $x );. No private methods found.

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PHP object-oriented polynomial least-square regression class. C template classes for matrix math. FFT for LibreOffice Calc. Fast Fourier Transform for LibreOffice Calc. Simple and fast Javascript graphing library. PHP object-oriented X/Y graphing class. PHP object-oriented Gauss-Newton curve fitting class. PHP Arbitrary precision BC math functions class. JQuery plug-in for a table-like format. Example of 3d rotation. A Javascript game similar to Ataxx and Reversi. A Javascript mouse speed game.

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DrQueNet is host to following sites. Pages designed by Andrew Que. PHP object-oriented polynomial least-square regression class. PHP Arbitrary precision BC math functions class. PHP object-oriented X/Y graphing class. PHP object-oriented Gauss-Newton curve fitting class. C template classes for matrix math. JQuery plug-in for a table-like format. A graphical walk-through to the King's Quest 1 remake. Detailed information about the Koei game. Information about the Konami game. How to breath fire. Sites no ...

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Polynomial Regression PHP class

A PHP regression class. Linear Regression with Forced Intercept. Not all data sets can be accurately modeled with polynomial regression regardless of the degree polynomial selected. It helps to have an understanding of the origin of the data and the function attempting to be modeled. Polynomials are one method of curve fitting. Some other methods are implemented with the Gauss-Newton class. The non-linear functions implemented are:. These classes are in beta. The key to weighting is to register a weighti...

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Monday, 20 August 2012. 1) Solve the equation (x. 8211; 5x – 7) (7x. 8211; 4x 10). 8211; 9x – 3 (B) 8x. 8211; 9x 3 (C) 3x. 9x 3 (D) 8x. 9x – 3. Calculator, make x = any number of your choice i.e. x= 1, 2, 3…………………………….100 or more i.e. x =9. ON] [9] [SHIFT] [STO] [X] (x=9). Note:-Please use the key [AC] during calculations after you press the key [ON] on any question given. AC] [(] [ALPHA] [X] [x. 5] [ALPHA] [X] [-] [7] [)] [(] [7] [ALPHA] [X] [x. 4] [ALPHA] [X] [1] [0] [)] [=] (570). 8211; 9x – 3.

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