import javastat.regression.glm.LogLinearRegression;

/**

*

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

* <p>Data Source: McCullagh, P. and Nelder, J. A. (1989).

* Generalized Linear Models. New York: Chapman and Hall, p. 205. </p>

*/

String[][] shipData = { {"a", "a", "a", "a", "a", "a", "a", "a",

"b", "b", "b", "b", "b", "b", "b", "b",

"c", "c", "c", "c", "c", "c", "c", "c",

"d", "d", "d", "d", "d", "d", "d", "d",

"e", "e", "e", "e", "e", "e", "e", "e"},

{"1960-64", "1960-64", "1965-69", "1965-69",

"1970-74", "1970-74", "1975-79", "1975-79",

"1960-64", "1960-64", "1965-69", "1965-69",

"1970-74", "1970-74", "1975-79", "1975-79",

"1960-64", "1960-64", "1965-69", "1965-69",

"1970-74", "1970-74", "1975-79", "1975-79",

"1960-64", "1960-64", "1965-69", "1965-69",

"1970-74", "1970-74", "1975-79", "1975-79",

"1960-64", "1960-64", "1965-69", "1965-69",

"1970-74", "1970-74", "1975-79", "1975-79"},

{"1960-74", "1975-79", "1960-74", "1975-79",

"1960-74", "1975-79", "1960-74", "1975-79",

"1960-74", "1975-79", "1960-74", "1975-79",

"1960-74", "1975-79", "1960-74", "1975-79",

"1960-74", "1975-79", "1960-74", "1975-79",

"1960-74", "1975-79", "1960-74", "1975-79",

"1960-74", "1975-79", "1960-74", "1975-79",

"1960-74", "1975-79", "1960-74", "1975-79",

"1960-74", "1975-79", "1960-74", "1975-79",

"1960-74", "1975-79", "1960-74", "1975-79"} };

double[] offset = {127, 63, 1095, 1095, 1512, 3353, 0, 2244, 44882,

17176, 28609, 20370, 7064, 13099, 0, 7177, 1179,

552, 781, 676, 783, 1948, 0, 274, 251, 105, 288,

192, 349, 1208, 0, 2051, 45, 0, 789, 437, 1157,

2161, 0, 542};

double[] damageNumber = {0, 0, 3, 4, 6, 18, 0, 11, 39, 29, 58, 53, 12,

44, 0, 18, 1, 1, 0, 1, 6, 2, 0, 1, 0, 0, 0, 0,

2, 11, 0, 4, 0, 0, 7, 7, 5, 12, 0, 1};

testclass1 = new LogLinearRegression(damageNumber, offset, shipData);

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] + " , " +

coefficients[4] + " , " + coefficients[5] + " , " +

coefficients[6] + " , " + coefficients[7] + " , "

coefficients[8] + "]");

testclass2 = new LogLinearRegression();

coefficients = testclass2.coefficients(damageNumber, offset, shipData);

confidenceInterval = testclass2.confidenceInterval(0.1, damageNumber,

offset, shipData);

testStatistic = testclass2.testStatistic(damageNumber, offset, shipData);

pValue = testclass2.pValue(damageNumber, offset, shipData);

devianceTable = testclass2.devianceTable(damageNumber, offset, shipData);

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

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

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

testStatistic[4] + " , " + testStatistic[5] + " , " +

testStatistic[6] + " , " + testStatistic[7] + " , " +

testStatistic[8] + "]");

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

+ pValue[0] + " , " + pValue[1] + " , " + pValue[2] + " , " + pValue[3] +

" , " + pValue[4] + " , " + pValue[5] + " , " + pValue[6] + " , " +

pValue[7] + " , " + pValue[8] + "]");

Results:

The estimated coefficients (non-null constructor)

= [-6.405 , -0.545, -0.688, -0.075 , 0.325 , 0.697 , 0.818 , 0.449 , 0.384]

The z statistics (null constructor)

= [-29.457, -3.068 , -2.091 , -0.258, 1.378, 4.658 , 4.817 , 1.926, 3.250]

The p-values for the z statistics (null constructor)

= [0.0 , 0.002, 0.036 , 0.796, 0.168, 3.196E-6 , 1.457E-6 , 0.054 , 0.001]