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https://issues.apache.org/jira/browse/MATH-1431?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]
Bruno P. Kinoshita updated MATH-1431:
-------------------------------------
Description:
The NaN can be reproduced by the following program. Evaluating at x = 0.3, it
appeared that getkernel returned a NormalDistribution with mean of NaN and
standardDeviation of NaN.
{code:java}
final int len = 240000;
double[] data = new double[len];
for (int i = 0; i < len / 2; ++i) {
data[i] = 0;
}
for (int i = len / 2 + 1; i < len ; ++i) {
data[i] = 1;
}
int binCnt = Math.max(1, data.length / 10);
EmpiricalDistribution edist = new EmpiricalDistribution(binCnt);
edist.load(data);
double x = 0.3;
double y = edist.cumulativeProbability(x);
System.out.println("y is " + y);
{code}
was:
The NaN can be reproduced by the following program. Evaluating at x = 0.3, it
appeared that getkernel returned a NormalDistribution with mean of NaN and
standardDeviation of NaN.
final int len = 240000;
double[] data = new double[len];
for (int i = 0; i < len / 2; ++i) {
data[i] = 0;
}
for (int i = len / 2 + 1; i < len ; ++i) {
data[i] = 1;
}
int binCnt = Math.max(1, data.length / 10);
EmpiricalDistribution edist = new EmpiricalDistribution(binCnt);
edist.load(data);
double x = 0.3;
double y = edist.cumulativeProbability(x);
System.out.println("y is " + y);
> EmpiricalDistribution cumulativeProbability can return NaN when evaluated
> within an empty bin.
> ----------------------------------------------------------------------------------------------
>
> Key: MATH-1431
> URL: https://issues.apache.org/jira/browse/MATH-1431
> Project: Commons Math
> Issue Type: Bug
> Affects Versions: 3.6.1
> Reporter: Jay
>
> The NaN can be reproduced by the following program. Evaluating at x = 0.3, it
> appeared that getkernel returned a NormalDistribution with mean of NaN and
> standardDeviation of NaN.
> {code:java}
> final int len = 240000;
> double[] data = new double[len];
> for (int i = 0; i < len / 2; ++i) {
> data[i] = 0;
> }
> for (int i = len / 2 + 1; i < len ; ++i) {
> data[i] = 1;
> }
> int binCnt = Math.max(1, data.length / 10);
> EmpiricalDistribution edist = new EmpiricalDistribution(binCnt);
> edist.load(data);
> double x = 0.3;
> double y = edist.cumulativeProbability(x);
> System.out.println("y is " + y);
> {code}
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