Initial Certified Tests for Univariate. Note UnivariateImpl currently fails
git-svn-id: https://svn.apache.org/repos/asf/jakarta/commons/proper/math/trunk@140876 13f79535-47bb-0310-9956-ffa450edef68
This commit is contained in:
Mark R. Diggory
parent
d23bf18b40
commit
60314410e2
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/* ====================================================================
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* The Apache Software License, Version 1.1
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*
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* Copyright (c) 2003 The Apache Software Foundation. All rights
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* reserved.
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*
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* Redistribution and use in source and binary forms, with or without
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* modification, are permitted provided that the following conditions
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* are met:
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*
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* 1. Redistributions of source code must retain the above copyright
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* notice, this list of conditions and the following disclaimer.
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*
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* 2. Redistributions in binary form must reproduce the above copyright
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* notice, this list of conditions and the following disclaimer in
|
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* the documentation and/or other materials provided with the
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* distribution.
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*
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* 3. The end-user documentation included with the redistribution, if
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* any, must include the following acknowlegement:
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* "This product includes software developed by the
|
||||
* Apache Software Foundation (http://www.apache.org/)."
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* Alternately, this acknowlegement may appear in the software itself,
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* if and wherever such third-party acknowlegements normally appear.
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*
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* 4. The names "The Jakarta Project", "Commons", and "Apache Software
|
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* Foundation" must not be used to endorse or promote products derived
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||||
* from this software without prior written permission. For written
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||||
* permission, please contact apache@apache.org.
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*
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* 5. Products derived from this software may not be called "Apache"
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* nor may "Apache" appear in their names without prior written
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* permission of the Apache Software Foundation.
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*
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* THIS SOFTWARE IS PROVIDED ``AS IS'' AND ANY EXPRESSED OR IMPLIED
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* WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES
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* OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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* DISCLAIMED. IN NO EVENT SHALL THE APACHE SOFTWARE FOUNDATION OR
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* ITS CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL,
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* SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT
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* LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF
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* USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND
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* ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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* OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT
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* OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF
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* SUCH DAMAGE.
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* ====================================================================
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*
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* This software consists of voluntary contributions made by many
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* individuals on behalf of the Apache Software Foundation. For more
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* information on the Apache Software Foundation, please see
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* <http://www.apache.org/>.
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*/
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package org.apache.commons.math.stat;
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import junit.framework.Test;
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import junit.framework.TestCase;
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import junit.framework.TestSuite;
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import java.io.BufferedReader;
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import java.io.File;
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import java.io.FileNotFoundException;
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import java.io.FileReader;
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import java.io.FilenameFilter;
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import java.io.IOException;
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import java.net.URL;
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import org.apache.commons.logging.*;
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/**
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* Test cases for the {@link Univariate} class.
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*
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* @author Mark R. Diggory
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* @version $Revision: 1.1 $ $Date: 2003/06/02 04:25:52 $
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*/
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public class CertifiedDataTest extends TestCase {
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protected double tolerance = .01;
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protected File[] dataFiles = null;
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protected Univariate u = null;
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protected double mean = Double.NaN;
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protected double std = Double.NaN;
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protected Log log = LogFactory.getLog(this.getClass());
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/**
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* Certified Data Test Constructor
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* @param name
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*/
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public CertifiedDataTest(String name) {
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super(name);
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setUp();
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}
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/* (non-Javadoc)
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* @see junit.framework.TestCase#setUp()
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*/
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public void setUp() {
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URL url = getClass().getResource("data");
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File file = new File(url.getFile());
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dataFiles = file.listFiles(new FilenameFilter() {
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public boolean accept(File dir, String name) {
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return name.endsWith(".dat");
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}
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});
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}
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/**
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* @return The test suite
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*/
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public static Test suite() {
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TestSuite suite = new TestSuite(CertifiedDataTest.class);
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suite.setName("Certified Tests");
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return suite;
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}
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/**
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* Test UnivariateImpl
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*/
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public void testUnivariateImpl() {
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for (int i = 0; i < dataFiles.length; i++) {
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u = new UnivariateImpl();
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loadStats(dataFiles[i]);
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assertEquals(
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dataFiles[i].getName() + ":std",
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std,
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u.getStandardDeviation(),
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tolerance);
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assertEquals(
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dataFiles[i].getName() + ":mean",
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mean,
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u.getMean(),
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tolerance);
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}
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}
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/**
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* Test UnivariateImpl
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*/
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public void testStoredUnivariateImpl() {
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for (int i = 0; i < dataFiles.length; i++) {
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u = new StoreUnivariateImpl();
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loadStats(dataFiles[i]);
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assertEquals(
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dataFiles[i].getName() + ":std",
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std,
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u.getStandardDeviation(),
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tolerance);
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assertEquals(
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dataFiles[i].getName() + ":mean",
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mean,
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u.getMean(),
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tolerance);
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}
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}
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/**
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* loads a Univariate off of a test file
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* @param file
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*/
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private void loadStats(File file) {
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try {
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u.clear();
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mean = Double.NaN;
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std = Double.NaN;
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BufferedReader in = new BufferedReader(new FileReader(file));
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String line = null;
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for (int j = 0; j < 60; j++) {
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line = in.readLine();
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if (j == 40) {
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mean =
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Double.parseDouble(
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line.substring(line.lastIndexOf(":") + 1).trim());
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}
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if (j == 41) {
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std =
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Double.parseDouble(
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line.substring(line.lastIndexOf(":") + 1).trim());
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}
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}
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line = in.readLine();
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while (line != null) {
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if(file.getName().equals("NumAcc4.dat")){
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System.out.println("Line: " + line);
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System.out.println("Mean: " + u.getMean());
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System.out.println("Std: " + u.getStandardDeviation());
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}
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u.addValue(Double.parseDouble(line.trim()));
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line = in.readLine();
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}
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in.close();
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System.out.println(" ");
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} catch (FileNotFoundException fnfe) {
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log.error(fnfe.getMessage(), fnfe);
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} catch (IOException ioe) {
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log.error(ioe.getMessage(), ioe);
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}
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}
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}
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@ -0,0 +1,260 @@
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File Name: Lew.dat
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File Format: ASCII
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Header : lines 1 to 60 (= 60)
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Certified Values: lines 41 to 43 (= 3)
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Data : lines 61 to 260 (= 200)
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Dataset Name: Lew (Beam Deflection Data)
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Description: This is an observed/"real world" data set
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consisting of 200 deflections of a steel-concrete
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beam while subjected to periodic pressure.
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The experimenter was H. S. Lew of the
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Center for Building Technology at NIST.
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We here use this data to test accuracy
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in summary statistics calculations.
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Stat Category: Univariate: Summary Statistics
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Reference: None
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Data: "Real World"
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1 Response : y = beam deflection
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0 Predictors
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200 Observations
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Model: Lower Level of Difficulty
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2 Parameters : mu, sigma
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1 Response Variable : y
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0 Predictor Variables
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y = mu + e
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Certified Values
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Sample Mean ybar: -177.435000000000
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Sample Standard Deviation (denom. = n-1) s: 277.332168044316
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Sample Autocorrelation Coefficient (lag 1) r(1): -0.307304800605679
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Number of Observations: 200
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Data: Y
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----------
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-213
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||||
-564
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||||
-35
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||||
-15
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141
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115
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||||
-420
|
||||
-360
|
||||
203
|
||||
-338
|
||||
-431
|
||||
194
|
||||
-220
|
||||
-513
|
||||
154
|
||||
-125
|
||||
-559
|
||||
92
|
||||
-21
|
||||
-579
|
||||
-52
|
||||
99
|
||||
-543
|
||||
-175
|
||||
162
|
||||
-457
|
||||
-346
|
||||
204
|
||||
-300
|
||||
-474
|
||||
164
|
||||
-107
|
||||
-572
|
||||
-8
|
||||
83
|
||||
-541
|
||||
-224
|
||||
180
|
||||
-420
|
||||
-374
|
||||
201
|
||||
-236
|
||||
-531
|
||||
83
|
||||
27
|
||||
-564
|
||||
-112
|
||||
131
|
||||
-507
|
||||
-254
|
||||
199
|
||||
-311
|
||||
-495
|
||||
143
|
||||
-46
|
||||
-579
|
||||
-90
|
||||
136
|
||||
-472
|
||||
-338
|
||||
202
|
||||
-287
|
||||
-477
|
||||
169
|
||||
-124
|
||||
-568
|
||||
17
|
||||
48
|
||||
-568
|
||||
-135
|
||||
162
|
||||
-430
|
||||
-422
|
||||
172
|
||||
-74
|
||||
-577
|
||||
-13
|
||||
92
|
||||
-534
|
||||
-243
|
||||
194
|
||||
-355
|
||||
-465
|
||||
156
|
||||
-81
|
||||
-578
|
||||
-64
|
||||
139
|
||||
-449
|
||||
-384
|
||||
193
|
||||
-198
|
||||
-538
|
||||
110
|
||||
-44
|
||||
-577
|
||||
-6
|
||||
66
|
||||
-552
|
||||
-164
|
||||
161
|
||||
-460
|
||||
-344
|
||||
205
|
||||
-281
|
||||
-504
|
||||
134
|
||||
-28
|
||||
-576
|
||||
-118
|
||||
156
|
||||
-437
|
||||
-381
|
||||
200
|
||||
-220
|
||||
-540
|
||||
83
|
||||
11
|
||||
-568
|
||||
-160
|
||||
172
|
||||
-414
|
||||
-408
|
||||
188
|
||||
-125
|
||||
-572
|
||||
-32
|
||||
139
|
||||
-492
|
||||
-321
|
||||
205
|
||||
-262
|
||||
-504
|
||||
142
|
||||
-83
|
||||
-574
|
||||
0
|
||||
48
|
||||
-571
|
||||
-106
|
||||
137
|
||||
-501
|
||||
-266
|
||||
190
|
||||
-391
|
||||
-406
|
||||
194
|
||||
-186
|
||||
-553
|
||||
83
|
||||
-13
|
||||
-577
|
||||
-49
|
||||
103
|
||||
-515
|
||||
-280
|
||||
201
|
||||
300
|
||||
-506
|
||||
131
|
||||
-45
|
||||
-578
|
||||
-80
|
||||
138
|
||||
-462
|
||||
-361
|
||||
201
|
||||
-211
|
||||
-554
|
||||
32
|
||||
74
|
||||
-533
|
||||
-235
|
||||
187
|
||||
-372
|
||||
-442
|
||||
182
|
||||
-147
|
||||
-566
|
||||
25
|
||||
68
|
||||
-535
|
||||
-244
|
||||
194
|
||||
-351
|
||||
-463
|
||||
174
|
||||
-125
|
||||
-570
|
||||
15
|
||||
72
|
||||
-550
|
||||
-190
|
||||
172
|
||||
-424
|
||||
-385
|
||||
198
|
||||
-218
|
||||
-536
|
||||
96
|
||||
|
|
@ -0,0 +1,278 @@
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File Name: Lottery.dat
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File Format: ASCII
|
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Header : lines 1 to 60 (= 60)
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Certified Values: lines 41 to 43 (= 3)
|
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Data : lines 61 to 278 (= 218)
|
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|
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Dataset Name: Lottery
|
||||
|
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Description: This is an observed/"real world" data set
|
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consisting of 218 lottery values
|
||||
from September 3, 1989 to April 14, 1990 (32 weeks).
|
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One 3-digit random number (from 000 to 999)
|
||||
is drawn per day, 7 days per week for most
|
||||
weeks, but fewer days per week for some weeks.
|
||||
We here use this data to test accuracy
|
||||
in summary statistics calculations.
|
||||
|
||||
Stat Category: Univariate: Summary Statistics
|
||||
|
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Reference: None
|
||||
|
||||
Data: "Real World"
|
||||
1 Response : y = 3-digit random number
|
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0 Predictors
|
||||
218 Observations
|
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|
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Model: Lower Level of Difficulty
|
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2 Parameters : mu, sigma
|
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1 Response Variable : y
|
||||
0 Predictor Variables
|
||||
|
||||
y = mu + e
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Certified Values
|
||||
Sample Mean ybar: 518.958715596330
|
||||
Sample Standard Deviation (denom. = n-1) s: 291.699727470969
|
||||
Sample Autocorrelation Coefficient (lag 1) r(1): -0.120948622967393
|
||||
|
||||
Number of Observations: 218
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Data: Y
|
||||
----------
|
||||
162
|
||||
671
|
||||
933
|
||||
414
|
||||
788
|
||||
730
|
||||
817
|
||||
33
|
||||
536
|
||||
875
|
||||
670
|
||||
236
|
||||
473
|
||||
167
|
||||
877
|
||||
980
|
||||
316
|
||||
950
|
||||
456
|
||||
92
|
||||
517
|
||||
557
|
||||
956
|
||||
954
|
||||
104
|
||||
178
|
||||
794
|
||||
278
|
||||
147
|
||||
773
|
||||
437
|
||||
435
|
||||
502
|
||||
610
|
||||
582
|
||||
780
|
||||
689
|
||||
562
|
||||
964
|
||||
791
|
||||
28
|
||||
97
|
||||
848
|
||||
281
|
||||
858
|
||||
538
|
||||
660
|
||||
972
|
||||
671
|
||||
613
|
||||
867
|
||||
448
|
||||
738
|
||||
966
|
||||
139
|
||||
636
|
||||
847
|
||||
659
|
||||
754
|
||||
243
|
||||
122
|
||||
455
|
||||
195
|
||||
968
|
||||
793
|
||||
59
|
||||
730
|
||||
361
|
||||
574
|
||||
522
|
||||
97
|
||||
762
|
||||
431
|
||||
158
|
||||
429
|
||||
414
|
||||
22
|
||||
629
|
||||
788
|
||||
999
|
||||
187
|
||||
215
|
||||
810
|
||||
782
|
||||
47
|
||||
34
|
||||
108
|
||||
986
|
||||
25
|
||||
644
|
||||
829
|
||||
630
|
||||
315
|
||||
567
|
||||
919
|
||||
331
|
||||
207
|
||||
412
|
||||
242
|
||||
607
|
||||
668
|
||||
944
|
||||
749
|
||||
168
|
||||
864
|
||||
442
|
||||
533
|
||||
805
|
||||
372
|
||||
63
|
||||
458
|
||||
777
|
||||
416
|
||||
340
|
||||
436
|
||||
140
|
||||
919
|
||||
350
|
||||
510
|
||||
572
|
||||
905
|
||||
900
|
||||
85
|
||||
389
|
||||
473
|
||||
758
|
||||
444
|
||||
169
|
||||
625
|
||||
692
|
||||
140
|
||||
897
|
||||
672
|
||||
288
|
||||
312
|
||||
860
|
||||
724
|
||||
226
|
||||
884
|
||||
508
|
||||
976
|
||||
741
|
||||
476
|
||||
417
|
||||
831
|
||||
15
|
||||
318
|
||||
432
|
||||
241
|
||||
114
|
||||
799
|
||||
955
|
||||
833
|
||||
358
|
||||
935
|
||||
146
|
||||
630
|
||||
830
|
||||
440
|
||||
642
|
||||
356
|
||||
373
|
||||
271
|
||||
715
|
||||
367
|
||||
393
|
||||
190
|
||||
669
|
||||
8
|
||||
861
|
||||
108
|
||||
795
|
||||
269
|
||||
590
|
||||
326
|
||||
866
|
||||
64
|
||||
523
|
||||
862
|
||||
840
|
||||
219
|
||||
382
|
||||
998
|
||||
4
|
||||
628
|
||||
305
|
||||
747
|
||||
247
|
||||
34
|
||||
747
|
||||
729
|
||||
645
|
||||
856
|
||||
974
|
||||
24
|
||||
568
|
||||
24
|
||||
694
|
||||
608
|
||||
480
|
||||
410
|
||||
729
|
||||
947
|
||||
293
|
||||
53
|
||||
930
|
||||
223
|
||||
203
|
||||
677
|
||||
227
|
||||
62
|
||||
455
|
||||
387
|
||||
318
|
||||
562
|
||||
242
|
||||
428
|
||||
968
|
||||
|
|
@ -0,0 +1,110 @@
|
|||
File Name: Mavro.dat
|
||||
|
||||
File Format: ASCII
|
||||
Header : lines 1 to 60 (= 60)
|
||||
Certified Values: lines 41 to 43 (= 3)
|
||||
Data : lines 61 to 110 (= 50)
|
||||
|
||||
Dataset Name: Mavro (Filter Transmittance Data)
|
||||
|
||||
Description: This is an observed/"real world" data set
|
||||
consisting of 50 transmittance measurements
|
||||
(at a sampling rate of 10 observations per second)
|
||||
from a filter with a nominal value of 2.
|
||||
The experimenter was Radu Mavrodineaunu,
|
||||
a member of the chemistry staff at NIST.
|
||||
We here use this data to test accuracy
|
||||
in summary statistics calculations.
|
||||
|
||||
Stat Category: Univariate: Summary Statistics
|
||||
|
||||
Reference: None
|
||||
|
||||
Data: "Real World"
|
||||
1 Response : y = transmittance
|
||||
0 Predictors
|
||||
50 Observations
|
||||
|
||||
Model: Lower Level of Difficulty
|
||||
2 Parameters : mu, sigma
|
||||
1 Response Variable : y
|
||||
0 Predictor Variables
|
||||
|
||||
y = mu + e
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Certified Values
|
||||
Sample Mean ybar: 2.00185600000000
|
||||
Sample Standard Deviation (denom. = n-1) s: 0.000429123454003053
|
||||
Sample Autocorrelation Coefficient (lag 1) r(1): 0.937989183438248
|
||||
|
||||
Number of Observations: 50
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Data: Y
|
||||
-------------
|
||||
2.00180
|
||||
2.00170
|
||||
2.00180
|
||||
2.00190
|
||||
2.00180
|
||||
2.00170
|
||||
2.00150
|
||||
2.00140
|
||||
2.00150
|
||||
2.00150
|
||||
2.00170
|
||||
2.00180
|
||||
2.00180
|
||||
2.00190
|
||||
2.00190
|
||||
2.00210
|
||||
2.00200
|
||||
2.00160
|
||||
2.00140
|
||||
2.00130
|
||||
2.00130
|
||||
2.00150
|
||||
2.00150
|
||||
2.00160
|
||||
2.00150
|
||||
2.00140
|
||||
2.00130
|
||||
2.00140
|
||||
2.00150
|
||||
2.00140
|
||||
2.00150
|
||||
2.00160
|
||||
2.00150
|
||||
2.00160
|
||||
2.00190
|
||||
2.00200
|
||||
2.00200
|
||||
2.00210
|
||||
2.00220
|
||||
2.00230
|
||||
2.00240
|
||||
2.00250
|
||||
2.00270
|
||||
2.00260
|
||||
2.00260
|
||||
2.00260
|
||||
2.00270
|
||||
2.00260
|
||||
2.00250
|
||||
2.00240
|
||||
|
|
@ -0,0 +1,160 @@
|
|||
File Name: Michelso.dat
|
||||
|
||||
File Format: ASCII
|
||||
Header : lines 1 to 60 (= 60)
|
||||
Certified Values: lines 41 to 43 (= 3)
|
||||
Data : lines 61 to 160 (= 100)
|
||||
|
||||
Dataset Name: Michelso (Speed of Light Data, in millions of meters per second)
|
||||
|
||||
Description: This is an observed/"real world" data set
|
||||
consisting of 100 measurements of the
|
||||
speed of light in air. This classic experiment
|
||||
was carried out by Michelson is 1879.
|
||||
We here use this data to test accuracy
|
||||
in summary statistics calculations.
|
||||
|
||||
Stat Category: Univariate: Summary Statistics
|
||||
|
||||
Reference: Dorsey, Ernest N. (1944). The Velocity of Light.
|
||||
Transactions of the American Philiosophical
|
||||
Society, Volume 34, Part 1, Pages 1-110, Table 22.
|
||||
|
||||
y = mu + e
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Certified Values
|
||||
Sample Mean ybar: 299.852400000000
|
||||
Sample Standard Deviation (denom. = n-1) s: 0.0790105478190518
|
||||
Sample Autocorrelation Coefficient (lag 1) r(1): 0.535199668621283
|
||||
|
||||
Number of Observations: 100
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Data: Y
|
||||
----------
|
||||
299.85
|
||||
299.74
|
||||
299.90
|
||||
300.07
|
||||
299.93
|
||||
299.85
|
||||
299.95
|
||||
299.98
|
||||
299.98
|
||||
299.88
|
||||
300.00
|
||||
299.98
|
||||
299.93
|
||||
299.65
|
||||
299.76
|
||||
299.81
|
||||
300.00
|
||||
300.00
|
||||
299.96
|
||||
299.96
|
||||
299.96
|
||||
299.94
|
||||
299.96
|
||||
299.94
|
||||
299.88
|
||||
299.80
|
||||
299.85
|
||||
299.88
|
||||
299.90
|
||||
299.84
|
||||
299.83
|
||||
299.79
|
||||
299.81
|
||||
299.88
|
||||
299.88
|
||||
299.83
|
||||
299.80
|
||||
299.79
|
||||
299.76
|
||||
299.80
|
||||
299.88
|
||||
299.88
|
||||
299.88
|
||||
299.86
|
||||
299.72
|
||||
299.72
|
||||
299.62
|
||||
299.86
|
||||
299.97
|
||||
299.95
|
||||
299.88
|
||||
299.91
|
||||
299.85
|
||||
299.87
|
||||
299.84
|
||||
299.84
|
||||
299.85
|
||||
299.84
|
||||
299.84
|
||||
299.84
|
||||
299.89
|
||||
299.81
|
||||
299.81
|
||||
299.82
|
||||
299.80
|
||||
299.77
|
||||
299.76
|
||||
299.74
|
||||
299.75
|
||||
299.76
|
||||
299.91
|
||||
299.92
|
||||
299.89
|
||||
299.86
|
||||
299.88
|
||||
299.72
|
||||
299.84
|
||||
299.85
|
||||
299.85
|
||||
299.78
|
||||
299.89
|
||||
299.84
|
||||
299.78
|
||||
299.81
|
||||
299.76
|
||||
299.81
|
||||
299.79
|
||||
299.81
|
||||
299.82
|
||||
299.85
|
||||
299.87
|
||||
299.87
|
||||
299.81
|
||||
299.74
|
||||
299.81
|
||||
299.94
|
||||
299.95
|
||||
299.80
|
||||
299.81
|
||||
299.87
|
||||
|
|
@ -0,0 +1,63 @@
|
|||
File Name: NumAcc1.dat
|
||||
|
||||
File Format: ASCII
|
||||
Header : lines 1 to 60 (= 60)
|
||||
Certified Values: lines 41 to 43 (= 3)
|
||||
Data : lines 61 to 63 (= 3)
|
||||
|
||||
Dataset Name: NumAcc1
|
||||
|
||||
Description: This is a constructed/fabricated data set
|
||||
to test accuracy in summary statistic calculations.
|
||||
The numbers are large (8-digit integers) and
|
||||
differ only in the last decimal place.
|
||||
Note--by construction, this data set has
|
||||
sample mean = 10000002 (exact)
|
||||
sample standard deviation = 1 (exact)
|
||||
sample autocorrelation coef. = -0.5 (exact)
|
||||
|
||||
Stat Category: Univariate: Summary Statistics
|
||||
|
||||
Reference: Simon, Stephen D. and Lesage, James P. (1989).
|
||||
Assessing the Accuracy of ANOVA Caluclations
|
||||
in Statistical Software", Computational
|
||||
Statistics & data Analysis, 8, pp. 325-332.
|
||||
|
||||
Data: Constructed
|
||||
1 Response : y
|
||||
0 Predictors
|
||||
3 Observations
|
||||
|
||||
Model: Lower Level of Difficulty
|
||||
2 Parameters : mu, sigma
|
||||
1 Response Variable : y
|
||||
0 Predictor Variables
|
||||
|
||||
y = mu + e
|
||||
|
||||
|
||||
|
||||
Certified Values
|
||||
Sample Mean ybar: 10000002
|
||||
Sample Standard Deviation (denom. = n-1) s: 1
|
||||
Sample Autocorrelation Coefficient (lag 1) r(1): -0.5
|
||||
|
||||
Number of Observations: 3
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
Data: Y
|
||||
---------
|
||||
10000001
|
||||
10000003
|
||||
10000002
|
||||
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
File diff suppressed because it is too large
Load Diff
Loading…
Reference in New Issue