public class GeographicallyWeightedRegression
extends java.lang.Object
Modifier and Type | Field and Description |
---|---|
double |
AdjustedrSquared
Adjusted rSquared of the entire regression
|
double |
bestMedian
best median established by the robust regression
|
MultiRegression.MultivariateRegression |
bestMultivariateRegression
best multi variate regression (as established by the robust regression
|
java.util.ArrayList<double[]> |
beta
regression related parameter: beta
|
double[] |
betaGeoMeanRegress
geometric mean regression
|
java.util.ArrayList<org.apache.commons.math3.stat.descriptive.DescriptiveStatistics> |
betaStat
regression related parameter: beta statistics
|
java.util.ArrayList<java.lang.Double> |
betaSummaryMax
regression related parameter: max
|
java.util.ArrayList<java.lang.Double> |
betaSummaryMean
regression related parameter: mean
|
java.util.ArrayList<java.lang.Double> |
betaSummaryMin
regression related parameter:min
|
MultiRegression.MultivariateRegression |
cleanedMultivariateRegression
multivariate regression without outliers
|
java.util.ArrayList<org.apache.commons.math3.stat.descriptive.DescriptiveStatistics> |
columnParameters
column
|
double |
fValue
r squared of the entire regression
|
MultiRegression.MultivariateRegression |
geoXtoY
geographical aware multivariate regression
|
MultiRegression.MultivariateRegression |
geoYtoX
geographical aware multivariate regression
|
org.apache.commons.math3.stat.regression.GLSMultipleLinearRegression |
GLSMultiReg
The GeographicallyWeightedRegression compute the georgraphically weighted, multivariate regression
|
java.util.ArrayList<java.util.ArrayList<java.lang.Double>> |
mpMaps
map
|
java.util.ArrayList<double[]> |
outliersX
x outliers
|
java.util.ArrayList<java.lang.Double> |
outliersY
y outliers
|
java.util.ArrayList<double[]> |
parametersStdErrors
stadard error
|
java.util.ArrayList<double[][]> |
parametersVariance
parameters' variance matrix
|
double |
r2Geo |
java.util.ArrayList<java.lang.Double> |
regressandVariance
regressand variance
|
java.util.ArrayList<double[]> |
residuals
vector of residuals
|
java.util.ArrayList<java.lang.Double> |
sigma
get a matrix of residuals' covariance
|
org.apache.commons.math3.stat.descriptive.DescriptiveStatistics |
statsX
statistics on x
|
org.apache.commons.math3.stat.descriptive.DescriptiveStatistics |
statsY
statistics on y
|
double[][] |
weight
weight
|
double[][] |
x2regress
x to regress
|
double[][] |
x2regressClean |
double[] |
y2regress
y to regress
|
double[] |
y2regressClean |
Constructor and Description |
---|
GeographicallyWeightedRegression(double[] localFile2regress,
double[][] remoteFile2regress,
java.util.HashMap<java.lang.Integer,double[][]> geographicallyWeights,
int sizeCol,
int sizeLine)
instanciate a multivariate regression using the samples provided in the routine
|
Modifier and Type | Method and Description |
---|---|
void |
buildRLSRegression()
Builds a new LinearRegression without outliers found by buildWeight
|
static int |
combinations(int n,
int r) |
void |
findBestMultipleRegression() |
void |
geometricMeanRegression() |
double |
getMyMedian(java.util.List<java.lang.Double> list) |
long |
getRandomSeed()
get the seed for the random number generator
|
double[][] |
getSampleFeatures(java.util.List<java.lang.Integer> sampleIndex,
int sampleSize) |
java.util.List<java.lang.Integer> |
getSampleIndex(int sampleSize) |
double[] |
getSamplePredictedVariables(java.util.List<java.lang.Integer> sampleIndex,
int sampleSize) |
int |
makeCumul(double[] in) |
void |
setRandomSeed(long randomseed)
Set the seed for the random number generator
|
public org.apache.commons.math3.stat.regression.GLSMultipleLinearRegression GLSMultiReg
public java.util.ArrayList<double[]> beta
public java.util.ArrayList<java.lang.Double> betaSummaryMin
public java.util.ArrayList<java.lang.Double> betaSummaryMax
public java.util.ArrayList<java.lang.Double> betaSummaryMean
public java.util.ArrayList<org.apache.commons.math3.stat.descriptive.DescriptiveStatistics> columnParameters
public java.util.ArrayList<java.util.ArrayList<java.lang.Double>> mpMaps
public java.util.ArrayList<org.apache.commons.math3.stat.descriptive.DescriptiveStatistics> betaStat
public java.util.ArrayList<double[]> residuals
public java.util.ArrayList<double[][]> parametersVariance
public java.util.ArrayList<double[]> parametersStdErrors
public java.util.ArrayList<java.lang.Double> regressandVariance
public double fValue
public double AdjustedrSquared
public java.util.ArrayList<java.lang.Double> sigma
public double[][] x2regress
public double[] y2regress
public double[][] weight
public double[][] x2regressClean
public double[] y2regressClean
public double[] betaGeoMeanRegress
public double r2Geo
public java.util.ArrayList<double[]> outliersX
public java.util.ArrayList<java.lang.Double> outliersY
public double bestMedian
public MultiRegression.MultivariateRegression bestMultivariateRegression
public MultiRegression.MultivariateRegression cleanedMultivariateRegression
public MultiRegression.MultivariateRegression geoYtoX
public MultiRegression.MultivariateRegression geoXtoY
public org.apache.commons.math3.stat.descriptive.DescriptiveStatistics statsY
public org.apache.commons.math3.stat.descriptive.DescriptiveStatistics statsX
public GeographicallyWeightedRegression(double[] localFile2regress, double[][] remoteFile2regress, java.util.HashMap<java.lang.Integer,double[][]> geographicallyWeights, int sizeCol, int sizeLine)
localFile2regress
- measurements colected locallyremoteFile2regress
- measurements provided by other devicesgeographicallyWeights
- weights to applysizeCol
- number of columnssizeLine
- number of linespublic void findBestMultipleRegression()
public void buildRLSRegression()
public void setRandomSeed(long randomseed)
randomseed
- the seedpublic long getRandomSeed()
public java.util.List<java.lang.Integer> getSampleIndex(int sampleSize)
public double[][] getSampleFeatures(java.util.List<java.lang.Integer> sampleIndex, int sampleSize)
public double[] getSamplePredictedVariables(java.util.List<java.lang.Integer> sampleIndex, int sampleSize)
public int makeCumul(double[] in)
public double getMyMedian(java.util.List<java.lang.Double> list)
public static int combinations(int n, int r)
public void geometricMeanRegression()