Source Code Cross Referenced for ChiSquareTestImpl.java in  » Science » Apache-commons-math-1.1 » org » apache » commons » math » stat » inference » Java Source Code / Java DocumentationJava Source Code and Java Documentation

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Java Source Code / Java Documentation » Science » Apache commons math 1.1 » org.apache.commons.math.stat.inference 
Source Cross Referenced  Class Diagram Java Document (Java Doc) 


001:        /*
002:         * Copyright 2004 The Apache Software Foundation.
003:         *
004:         * Licensed under the Apache License, Version 2.0 (the "License");
005:         * you may not use this file except in compliance with the License.
006:         * You may obtain a copy of the License at
007:         *
008:         *      http://www.apache.org/licenses/LICENSE-2.0
009:         *
010:         * Unless required by applicable law or agreed to in writing, software
011:         * distributed under the License is distributed on an "AS IS" BASIS,
012:         * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
013:         * See the License for the specific language governing permissions and
014:         * limitations under the License.
015:         */
016:        package org.apache.commons.math.stat.inference;
017:
018:        import org.apache.commons.math.MathException;
019:        import org.apache.commons.math.distribution.DistributionFactory;
020:        import org.apache.commons.math.distribution.ChiSquaredDistribution;
021:
022:        /**
023:         * Implements Chi-Square test statistics defined in the {@link ChiSquareTest} interface.
024:         *
025:         * @version $Revision: 155427 $ $Date: 2005-02-26 06:11:52 -0700 (Sat, 26 Feb 2005) $
026:         */
027:        public class ChiSquareTestImpl implements  ChiSquareTest {
028:
029:            /** Cached DistributionFactory used to create ChiSquaredDistribution instances */
030:            private DistributionFactory distributionFactory = null;
031:
032:            /**
033:             * Construct a ChiSquareTestImpl 
034:             */
035:            public ChiSquareTestImpl() {
036:                super ();
037:            }
038:
039:            /**
040:             * @param observed array of observed frequency counts
041:             * @param expected array of expected frequency counts
042:             * @return chi-square test statistic
043:             * @throws IllegalArgumentException if preconditions are not met
044:             * or length is less than 2
045:             */
046:            public double chiSquare(double[] expected, long[] observed)
047:                    throws IllegalArgumentException {
048:                double sumSq = 0.0d;
049:                double dev = 0.0d;
050:                if ((expected.length < 2)
051:                        || (expected.length != observed.length)) {
052:                    throw new IllegalArgumentException(
053:                            "observed, expected array lengths incorrect");
054:                }
055:                if (!isPositive(expected) || !isNonNegative(observed)) {
056:                    throw new IllegalArgumentException(
057:                            "observed counts must be non-negative and expected counts must be postive");
058:                }
059:                for (int i = 0; i < observed.length; i++) {
060:                    dev = ((double) observed[i] - expected[i]);
061:                    sumSq += dev * dev / expected[i];
062:                }
063:                return sumSq;
064:            }
065:
066:            /**
067:             * @param observed array of observed frequency counts
068:             * @param expected array of exptected frequency counts
069:             * @return p-value
070:             * @throws IllegalArgumentException if preconditions are not met
071:             * @throws MathException if an error occurs computing the p-value
072:             */
073:            public double chiSquareTest(double[] expected, long[] observed)
074:                    throws IllegalArgumentException, MathException {
075:                ChiSquaredDistribution chiSquaredDistribution = getDistributionFactory()
076:                        .createChiSquareDistribution(
077:                                (double) expected.length - 1);
078:                return 1 - chiSquaredDistribution
079:                        .cumulativeProbability(chiSquare(expected, observed));
080:            }
081:
082:            /**
083:             * @param observed array of observed frequency counts
084:             * @param expected array of exptected frequency counts
085:             * @param alpha significance level of the test
086:             * @return true iff null hypothesis can be rejected with confidence
087:             * 1 - alpha
088:             * @throws IllegalArgumentException if preconditions are not met
089:             * @throws MathException if an error occurs performing the test
090:             */
091:            public boolean chiSquareTest(double[] expected, long[] observed,
092:                    double alpha) throws IllegalArgumentException,
093:                    MathException {
094:                if ((alpha <= 0) || (alpha > 0.5)) {
095:                    throw new IllegalArgumentException(
096:                            "bad significance level: " + alpha);
097:                }
098:                return (chiSquareTest(expected, observed) < alpha);
099:            }
100:
101:            /**
102:             * @param counts array representation of 2-way table
103:             * @return chi-square test statistic
104:             * @throws IllegalArgumentException if preconditions are not met
105:             */
106:            public double chiSquare(long[][] counts)
107:                    throws IllegalArgumentException {
108:
109:                checkArray(counts);
110:                int nRows = counts.length;
111:                int nCols = counts[0].length;
112:
113:                // compute row, column and total sums
114:                double[] rowSum = new double[nRows];
115:                double[] colSum = new double[nCols];
116:                double total = 0.0d;
117:                for (int row = 0; row < nRows; row++) {
118:                    for (int col = 0; col < nCols; col++) {
119:                        rowSum[row] += (double) counts[row][col];
120:                        colSum[col] += (double) counts[row][col];
121:                        total += (double) counts[row][col];
122:                    }
123:                }
124:
125:                // compute expected counts and chi-square
126:                double sumSq = 0.0d;
127:                double expected = 0.0d;
128:                for (int row = 0; row < nRows; row++) {
129:                    for (int col = 0; col < nCols; col++) {
130:                        expected = (rowSum[row] * colSum[col]) / total;
131:                        sumSq += (((double) counts[row][col] - expected) * ((double) counts[row][col] - expected))
132:                                / expected;
133:                    }
134:                }
135:                return sumSq;
136:            }
137:
138:            /**
139:             * @param counts array representation of 2-way table
140:             * @return p-value
141:             * @throws IllegalArgumentException if preconditions are not met
142:             * @throws MathException if an error occurs computing the p-value
143:             */
144:            public double chiSquareTest(long[][] counts)
145:                    throws IllegalArgumentException, MathException {
146:                checkArray(counts);
147:                double df = ((double) counts.length - 1)
148:                        * ((double) counts[0].length - 1);
149:                ChiSquaredDistribution chiSquaredDistribution = getDistributionFactory()
150:                        .createChiSquareDistribution(df);
151:                return 1 - chiSquaredDistribution
152:                        .cumulativeProbability(chiSquare(counts));
153:            }
154:
155:            /**
156:             * @param counts array representation of 2-way table
157:             * @param alpha significance level of the test
158:             * @return true iff null hypothesis can be rejected with confidence
159:             * 1 - alpha
160:             * @throws IllegalArgumentException if preconditions are not met
161:             * @throws MathException if an error occurs performing the test
162:             */
163:            public boolean chiSquareTest(long[][] counts, double alpha)
164:                    throws IllegalArgumentException, MathException {
165:                if ((alpha <= 0) || (alpha > 0.5)) {
166:                    throw new IllegalArgumentException(
167:                            "bad significance level: " + alpha);
168:                }
169:                return (chiSquareTest(counts) < alpha);
170:            }
171:
172:            /**
173:             * Checks to make sure that the input long[][] array is rectangular,
174:             * has at least 2 rows and 2 columns, and has all non-negative entries,
175:             * throwing IllegalArgumentException if any of these checks fail.
176:             * 
177:             * @param in input 2-way table to check
178:             * @throws IllegalArgumentException if the array is not valid
179:             */
180:            private void checkArray(long[][] in)
181:                    throws IllegalArgumentException {
182:
183:                if (in.length < 2) {
184:                    throw new IllegalArgumentException(
185:                            "Input table must have at least two rows");
186:                }
187:
188:                if (in[0].length < 2) {
189:                    throw new IllegalArgumentException(
190:                            "Input table must have at least two columns");
191:                }
192:
193:                if (!isRectangular(in)) {
194:                    throw new IllegalArgumentException(
195:                            "Input table must be rectangular");
196:                }
197:
198:                if (!isNonNegative(in)) {
199:                    throw new IllegalArgumentException(
200:                            "All entries in input 2-way table must be non-negative");
201:                }
202:
203:            }
204:
205:            //---------------------  Protected methods ---------------------------------
206:            /**
207:             * Gets a DistributionFactory to use in creating ChiSquaredDistribution instances.
208:             * 
209:             * @return a DistributionFactory
210:             */
211:            protected DistributionFactory getDistributionFactory() {
212:                if (distributionFactory == null) {
213:                    distributionFactory = DistributionFactory.newInstance();
214:                }
215:                return distributionFactory;
216:            }
217:
218:            //---------------------  Private array methods -- should find a utility home for these
219:
220:            /**
221:             * Returns true iff input array is rectangular.
222:             * 
223:             * @param in array to be tested
224:             * @return true if the array is rectangular
225:             * @throws NullPointerException if input array is null
226:             * @throws ArrayIndexOutOfBoundsException if input array is empty
227:             */
228:            private boolean isRectangular(long[][] in) {
229:                for (int i = 1; i < in.length; i++) {
230:                    if (in[i].length != in[0].length) {
231:                        return false;
232:                    }
233:                }
234:                return true;
235:            }
236:
237:            /**
238:             * Returns true iff all entries of the input array are > 0.
239:             * Returns true if the array is non-null, but empty
240:             * 
241:             * @param in array to be tested
242:             * @return true if all entries of the array are positive
243:             * @throws NullPointerException if input array is null
244:             */
245:            private boolean isPositive(double[] in) {
246:                for (int i = 0; i < in.length; i++) {
247:                    if (in[i] <= 0) {
248:                        return false;
249:                    }
250:                }
251:                return true;
252:            }
253:
254:            /**
255:             * Returns true iff all entries of the input array are >= 0.
256:             * Returns true if the array is non-null, but empty
257:             * 
258:             * @param in array to be tested
259:             * @return true if all entries of the array are non-negative
260:             * @throws NullPointerException if input array is null
261:             */
262:            private boolean isNonNegative(long[] in) {
263:                for (int i = 0; i < in.length; i++) {
264:                    if (in[i] < 0) {
265:                        return false;
266:                    }
267:                }
268:                return true;
269:            }
270:
271:            /**
272:             * Returns true iff all entries of (all subarrays of) the input array are >= 0.
273:             * Returns true if the array is non-null, but empty
274:             * 
275:             * @param in array to be tested
276:             * @return true if all entries of the array are non-negative
277:             * @throws NullPointerException if input array is null
278:             */
279:            private boolean isNonNegative(long[][] in) {
280:                for (int i = 0; i < in.length; i++) {
281:                    for (int j = 0; j < in[i].length; j++) {
282:                        if (in[i][j] < 0) {
283:                            return false;
284:                        }
285:                    }
286:                }
287:                return true;
288:            }
289:
290:        }
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