import javastat.regression.glm.LogisticRegression;

/**

*

* <p>Example: class LogisticRegression.</p>

*/

String[][] nominalCovariate = { {"a", "a", "b", "b", "c", "c", "a", "a",

"b", "c", "c", "c"},

{"T", "T", "T", "F", "T", "F", "T", "F",

"F", "T", "F", "F"} };

String[] stringBinaryResponse = {"s", "d", "s", "d", "s", "d", "d",

"s", "d", "s", "d", "d"};

testclass1 = new LogisticRegression(stringBinaryResponse, nominalCovariate);

coefficients = testclass1.coefficients;

confidenceInterval = testclass1.confidenceInterval;

testStatistic = testclass1.testStatistic;

pValue = testclass1.pValue;

devianceTable = testclass1.devianceTable;

print("The estimated coefficients (non-null constructor) = [" +

coefficients[0] + " , " + coefficients[1] + " , " +

coefficients[2] + " , " + coefficients[3] + "]");

testclass2 = new LogisticRegression();

coefficients = testclass2.coefficients(stringBinaryResponse, nominalCovariate);

confidenceInterval = testclass2.confidenceInterval(0.1, stringBinaryResponse,

nominalCovariate);

testStatistic = testclass2.testStatistic(stringBinaryResponse,

nominalCovariate);

pValue = testclass2.pValue(stringBinaryResponse, nominalCovariate);

devianceTable = testclass2.devianceTable(stringBinaryResponse,

nominalCovariate);

print("The z statistics (null constructor) = ["

+ testStatistic[0] + " , " + testStatistic[1] + " , " +

testStatistic[2] + " , " + testStatistic[3] + "]");

print("The p-values for the z statistics (null constructor) = ["

+ pValue[0] + " , " + pValue[1] + " , " +

pValue[2] + " , " + pValue[3] + "]");

Results:

The estimate for the first observation (non-null constructor) = 0.885

The confidence interval corresponding to the first observation (non-null

constructor) = [0.762, 1.0]

The estimate for the first observation under proportional hazards assumption

= 0.952

The estimated coefficients (non-null constructor) = [-1.928, 0.259, 0.447 , 2.436]

The z statistics (null constructor) = [-1.118, 0.135, 0.269, 1.594]

The p-values for the z statistics (null constructor) = [0.263 , 0.893, 0.788 , 0.111]