SCIP
Solving Constraint Integer Programs
Solving Constraint Integer Programs
public methods for statistical tests
Below are the public methods for statistical tests inside of SCIP
Functions | |
| SCIP_Real | SCIPstudentTGetCriticalValue (SCIP_CONFIDENCELEVEL clevel, int df) |
| SCIP_Real | SCIPcomputeTwoSampleTTestValue (SCIP_Real meanx, SCIP_Real meany, SCIP_Real variancex, SCIP_Real variancey, SCIP_Real countx, SCIP_Real county) |
| SCIP_Real | SCIPerf (SCIP_Real x) |
| SCIP_Real | SCIPnormalGetCriticalValue (SCIP_CONFIDENCELEVEL clevel) |
| SCIP_Real | SCIPnormalCDF (SCIP_Real mean, SCIP_Real variance, SCIP_Real value) |
| SCIP_Real SCIPstudentTGetCriticalValue | ( | SCIP_CONFIDENCELEVEL | clevel, |
| int | df | ||
| ) |
get critical value of a Student-T distribution for a given number of degrees of freedom at a confidence level
| clevel | (one-sided) confidence level |
| df | degrees of freedom |
Definition at line 94 of file misc.c.
References studentt_maxdf, studentt_quartiles, and studentt_quartilesabove.
Referenced by SCIPvarCalcPscostConfidenceBound(), and SCIPvarSignificantPscostDifference().
| SCIP_Real SCIPcomputeTwoSampleTTestValue | ( | SCIP_Real | meanx, |
| SCIP_Real | meany, | ||
| SCIP_Real | variancex, | ||
| SCIP_Real | variancey, | ||
| SCIP_Real | countx, | ||
| SCIP_Real | county | ||
| ) |
compute a t-value for the hypothesis that x and y are from the same population; Assuming that x and y represent normally distributed random samples with equal variance, the returned value comes from a Student-T distribution with countx + county - 2 degrees of freedom; this value can be compared with a critical value (see also SCIPstudentTGetCriticalValue()) at a predefined confidence level for checking if x and y significantly differ in location
| meanx | the mean of the first distribution |
| meany | the mean of the second distribution |
| variancex | the variance of the x-distribution |
| variancey | the variance of the y-distribution |
| countx | number of samples of x |
| county | number of samples of y |
Definition at line 111 of file misc.c.
References MAX, SCIP_INVALID, and SCIP_Real.
Referenced by SCIPvarSignificantPscostDifference().
returns the value of the Gauss error function evaluated at a given point
| x | value to evaluate |
Definition at line 144 of file misc.c.
References exp(), REALABS, SCIP_Real, and sign().
Referenced by SCIPcalcCumulativeDistribution(), and SCIPnormalCDF().
| SCIP_Real SCIPnormalGetCriticalValue | ( | SCIP_CONFIDENCELEVEL | clevel | ) |
get critical value of a standard normal distribution at a given confidence level
| clevel | (one-sided) confidence level |
Definition at line 171 of file misc.c.
References studentt_quartilesabove.
calculates the cumulative distribution P(-infinity <= x <= value) that a normally distributed random variable x takes a value between -infinity and parameter value.
The distribution is given by the respective mean and deviation. This implementation uses the error function erf().
calculates the cumulative distribution P(-infinity <= x <= value) that a normally distributed random variable x takes a value between -infinity and parameter value.
The distribution is given by the respective mean and deviation. This implementation uses the error function SCIPerf().
| mean | the mean value of the distribution |
| variance | the square of the deviation of the distribution |
| value | the upper limit of the calculated distribution integral |
Definition at line 184 of file misc.c.
References SCIP_Real, SCIPdebugMessage, SCIPerf(), sqrt(), and SQRTOFTWO.
Referenced by SCIPvarPscostThresholdProbabilityTest().