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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF licenses this file to You under the Apache License, Version 2.0
 * (the "License"); you may not use this file except in compliance with
 * the License.  You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
/**
 * Generic univariate and multivariate summary statistic objects.
 *
 * 

UnivariateStatistic API Usage Examples:

* *

UnivariateStatistic:

* * /∗ evaluation approach ∗/
* double[] values = new double[] { 1, 2, 3, 4, 5 };
* UnivariateStatistic stat = new Mean();
* out.println("mean = " + stat.evaluate(values));
*
* *

StorelessUnivariateStatistic:

* * /∗ incremental approach ∗/
* double[] values = new double[] { 1, 2, 3, 4, 5 };
* StorelessUnivariateStatistic stat = new Mean();
* out.println("mean before adding a value is NaN = " + stat.getResult());
* for (int i = 0; i < values.length; i++) {
*     stat.increment(values[i]);
*     out.println("current mean = " + stat2.getResult());
* }
* stat.clear();
* out.println("mean after clear is NaN = " + stat.getResult()); *
*/ package org.hipparchus.stat.descriptive;




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