PARP Research Group | Universidad de Murcia |
Statistics
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Classes | |
class | QVRANSAC< Element, Model > |
Implementation of RANSAC, a robust statistical model fitting algorithm. More... | |
class | QVPROSAC< Element, Model > |
Implementation of PROSAC, an extension to RANSAC (see QVRANSAC). More... | |
Functions | |
double | BhattacharyyaDistance (const QVVector &m1, const QVMatrix &S1, const QVVector &m2, const QVMatrix &S2) |
Obtains the Bhattacharyya distance of two gaussian distributions. | |
QVVector | qvLinearRegularizedRegression (const QVMatrix &A, const QVVector &b, const QVMatrix &Gamma=QVMatrix()) |
Estimates linear regression using Tikhonov regularization | |
double | randomNormalValue (const double mean, const double variance) |
Generate a normally distributed random number. |
Statistics, regression and model fitting related functionality.
double BhattacharyyaDistance | ( | const QVVector & | m1, | |
const QVMatrix & | S1, | |||
const QVVector & | m2, | |||
const QVMatrix & | S2 | |||
) |
Obtains the Bhattacharyya distance of two gaussian distributions.
Obtains the Bhattacharyya distance between two Gaussian distributions, given by their mean vectors and covariance matrices.
m1 | first mean. | |
S1 | first covariance matrix. | |
m2 | second mean. | |
S2 | second covariance matrix. |
Definition at line 28 of file qvstatistics.cpp.
QVVector qvLinearRegularizedRegression | ( | const QVMatrix & | A, | |
const QVVector & | b, | |||
const QVMatrix & | Gamma = QVMatrix() | |||
) |
Estimates linear regression using Tikhonov regularization
This function solves an overdetermined system of linear equations, given as:
avoiding ill conditioned cases by minimizing the following regularized expression:
Where the matrix is called the Tikhonov matrix. In many cases, it is convenient to use the identity matrix as the matrix.
A | Coefficients matrix. | |
b | Objective values vector. | |
Gamma | Tikhonov Matrix. If no value is provided, an identity matrix with adequate dimensions will be used in the regularized expression. |
Definition at line 37 of file qvstatistics.cpp.
double randomNormalValue | ( | const double | mean, | |
const double | variance | |||
) |
Generate a normally distributed random number.
This function uses the Box-Muller transform to generate independent samples of a normal distribution, provided its mean and variance parameters.
mean | Mean of the normal distribution. | |
variance | Variance of the normal distribution. |
Definition at line 44 of file qvstatistics.cpp.