Package org.apache.commons.math3.distribution

Examples of org.apache.commons.math3.distribution.PoissonDistribution.cumulativeProbability()

126
127
128
129
130
131
132
133
134
135
136
        final AnovaStats a = anovaStats(categoryData);
        // No try-catch or advertised exception because args are valid
        // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
        final FDistribution fdist = new FDistribution(null, a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);

    }

    /**
     * Computes the ANOVA P-value for a collection of {@link SummaryStatistics}.
View Full Code Here
168
169
170
171
172
173
174
175
176
177
178
               ConvergenceException, MaxCountExceededException {

        final AnovaStats a = anovaStats(categoryData, allowOneElementData);
        // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
        final FDistribution fdist = new FDistribution(null, a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);

    }

    /**
     * This method calls the method that actually does the calculations (except
View Full Code Here
124
125
126
127
128
129
130
131
132
133
134
        throws NullArgumentException, DimensionMismatchException,
        ConvergenceException, MaxCountExceededException {

        AnovaStats a = anovaStats(categoryData);
        FDistribution fdist = new FDistribution(a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);

    }

    /**
     * Performs an ANOVA test, evaluating the null hypothesis that there
View Full Code Here
126
127
128
129
130
131
132
133
134
135
136
        ConvergenceException, MaxCountExceededException {

        AnovaStats a = anovaStats(categoryData);
        // No try-catch or advertised exception because args are valid
        FDistribution fdist = new FDistribution(a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);

    }

    /**
     * Computes the ANOVA P-value for a collection of {@link SummaryStatistics}.
View Full Code Here
167
168
169
170
171
172
173
174
175
176
177
        throws NullArgumentException, DimensionMismatchException,
               ConvergenceException, MaxCountExceededException {

        final AnovaStats a = anovaStats(categoryData, allowOneElementData);
        final FDistribution fdist = new FDistribution(a.dfbg, a.dfwg);
        return 1.0 - fdist.cumulativeProbability(a.F);

    }

    /**
     * This method calls the method that actually does the calculations (except
View Full Code Here
254
255
256
257
258
259
260
261
262
263
264
        // No try-catch or advertised exception because args are valid
        // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
        final NormalDistribution standardNormal = new NormalDistribution(null, 0, 1);

        return 2*standardNormal.cumulativeProbability(z);
    }

    /**
     * Returns the <i>observed significance level</i>, or <a href=
     * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue">
 
View Full Code Here
182
183
184
185
186
187
188
189
190
191
192
        // No try-catch or advertised exception because args are valid
        // pass a null rng to avoid unneeded overhead as we will not sample from this distribution
        final NormalDistribution standardNormal = new NormalDistribution(null, 0, 1);

        return 2 * standardNormal.cumulativeProbability(z);
    }

    /**
     * Returns the asymptotic <i>observed significance level</i>, or <a href=
     * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue">
 
View Full Code Here
178
179
180
181
182
183
184
185
186
187
188
        final double z = (Umin - EU) / FastMath.sqrt(VarU);

        final NormalDistribution standardNormal = new NormalDistribution(0, 1);

        return 2 * standardNormal.cumulativeProbability(z);
    }

    /**
     * Returns the asymptotic <i>observed significance level</i>, or <a href=
     * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue">
 
View Full Code Here
253
254
255
256
257
258
259
260
261
262
263
        // - 0.5 is a continuity correction
        final double z = (Wmin - ES - 0.5) / FastMath.sqrt(VarS);

        final NormalDistribution standardNormal = new NormalDistribution(0, 1);

        return 2*standardNormal.cumulativeProbability(z);
    }

    /**
     * Returns the <i>observed significance level</i>, or <a href=
     * "http://www.cas.lancs.ac.uk/glossary_v1.1/hyptest.html#pvalue">
 
View Full Code Here
454
455
456
457
458
459
460
461
462
463
464
         *  Start with upper and lower tail bins.
         *  Lower bin = [0, lower); Upper bin = [upper, +inf).
         */
        PoissonDistribution poissonDistribution = new PoissonDistribution(mean);
        int lower = 1;
        while (poissonDistribution.cumulativeProbability(lower - 1) * sampleSize < minExpectedCount) {
            lower++;
        }
        int upper = (int) (5 * mean);  // Even for mean = 1, not much mass beyond 5
        while ((1 - poissonDistribution.cumulativeProbability(upper - 1)) * sampleSize < minExpectedCount) {
            upper--;
View Full Code Here
TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.