Package weka.core.matrix

Examples of weka.core.matrix.DoubleVector.minusEquals()

205
206
207
208
209
210
211
212
213
214
215
  public double  empiricalBayesEstimate ( double x ) {
    if( Math.abs(x) > 10 ) return x; // pratical consideration; modify later
    DoubleVector d =
    Maths.dnormLog( x, mixingDistribution.getPointValues(), 1 );
   
    d.minusEquals( d.max() );
    d = d.map("java.lang.Math", "exp");
    d.timesEquals( mixingDistribution.getFunctionValues() );
    return mixingDistribution.getPointValues().innerProduct( d ) / d.sum();
  }
View Full Code Here
282
283
284
285
286
287
288
289
290
291
292
  public double hf( double x ) {
    DoubleVector points = mixingDistribution.getPointValues();
    DoubleVector values = mixingDistribution.getFunctionValues();

    DoubleVector d = Maths.dnormLog( x, points, 1 );
    d.minusEquals( d.max() );

    d = (DoubleVector) d.map("java.lang.Math", "exp");
    d.timesEquals( values ); 

    return ((DoubleVector) points.times(2*x).minusEquals(x*x))
 
View Full Code Here
243
244
245
246
247
248
249
250
251
252
253
    DoubleVector points = mixingDistribution.getPointValues();
    DoubleVector values = mixingDistribution.getFunctionValues();
    DoubleVector mean = points.sqrt();
 
    DoubleVector d = Maths.dchisqLog( x, points );
    d.minusEquals( d.max() );
    d = d.map("java.lang.Math", "exp").timesEquals( values );
    double atilde = mean.innerProduct( d ) / d.sum();
    return atilde * atilde;
  }

View Full Code Here
329
330
331
332
333
334
335
336
337
338
339
    double x = Math.sqrt( AHat );
    DoubleVector mean = points.sqrt();
    DoubleVector d1 = Maths.dnormLog( x, mean, 1 );
    double d1max = d1.max();
    d1.minusEquals( d1max );
    DoubleVector d2 = Maths.dnormLog( -x, mean, 1 );
    d2.minusEquals( d1max );

    d1 = d1.map("java.lang.Math", "exp");
    d1.timesEquals( values ); 
View Full Code Here
331
332
333
334
335
336
337
338
339
340
341
    DoubleVector mean = points.sqrt();
    DoubleVector d1 = Maths.dnormLog( x, mean, 1 );
    double d1max = d1.max();
    d1.minusEquals( d1max );
    DoubleVector d2 = Maths.dnormLog( -x, mean, 1 );
    d2.minusEquals( d1max );

    d1 = d1.map("java.lang.Math", "exp");
    d1.timesEquals( values ); 
    d2 = d2.map("java.lang.Math", "exp");
    d2.timesEquals( values ); 
View Full Code Here
TOP
Copyright © 2018 www.massapi.com. All rights reserved.
All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.