Example usage for org.apache.commons.math3.linear ArrayRealVector getMinValue

Introduction

In this page you can find the example usage for org.apache.commons.math3.linear ArrayRealVector getMinValue.

Prototype

public double getMinValue() 

Source Link

Document

Get the value of the minimum entry.

Usage

From source file:gamlss.smoothing.PB.java

/**
* Constructs the base matrix./* ww w .j  ava 2 s . c  om*/
* @param colValues - values of the certain column of
*  the smooth matrix which corresponds to the 
*  currently fitting distribution parameter
* @return - base matrix
*/
//bbase <- function(x, xl, xr, ndx, deg, quantiles=FALSE)
private static BlockRealMatrix formX(final ArrayRealVector colValues) {

    //control$inter <- if (lx<99) 10 else control$inter # 
    //this is to prevent singularities when length(x) is small
    if (colValues.getDimension() < 99) {
        Controls.INTER = 10;
    }

    //xl <- min(x)
    double xl = colValues.getMinValue();

    //xr <- max(x)
    double xr = colValues.getMaxValue();

    //xmax <- xr + 0.01 * (xr - xl)
    double xmax = xr + 0.01 * (xr - xl);

    //xmin <- xl - 0.01 * (xr - xl)
    double xmin = xl - 0.01 * (xr - xl);

    //dx <- (xr - xl) / ndx
    double dx = (xmax - xmin) / Controls.INTER;

    //if (quantiles) # if true use splineDesign
    if (Controls.QUANTILES) {
        //knots <-  sort(c(seq(xl-deg*dx, xl, dx),quantile(x, 
        //prob=seq(0, 1, length=ndx)), seq(xr, xr+deg*dx, dx))) 
        ArrayRealVector kts = null;

        //B <- splineDesign(knots, x = x, outer.ok = TRUE, ord=deg+1)
        //return(B)  
        return null;
    } else {

        //kts <-   seq(xl - deg * dx, xr + deg * dx, by = dx)
        //ArrayRealVector kts = new ArrayRealVector(
        //ArithmeticSeries.getSeries(xl-deg*dx, xr+deg*dx, dx),false);

        rConnection.assingVar("min", new double[] { xmin - Controls.DEGREE * dx });
        rConnection.assingVar("max", new double[] { xmax + Controls.DEGREE * dx });
        rConnection.assingVar("step", new double[] { dx });

        ArrayRealVector kts = new ArrayRealVector(
                rConnection.runEvalDoubles("knots <- seq(min, max, by = step)"));

        //P <- outer(x, kts, FUN = tpower, deg)
        BlockRealMatrix pM = MatrixFunctions.outertpowerPB(colValues, kts, Controls.DEGREE);

        //D <- diff(diag(dim(P)[2]), 
        //diff = deg + 1) / (gamma(deg + 1) * dx ^ deg)
        BlockRealMatrix tempM = MatrixFunctions
                .diff(MatrixFunctions.buildIdentityMatrix(pM.getColumnDimension()), Controls.DEGREE + 1);

        double[][] tempArrArr = new double[tempM.getRowDimension()][tempM.getColumnDimension()];
        for (int i = 0; i < tempArrArr.length; i++) {
            for (int j = 0; j < tempArrArr[i].length; j++) {
                tempArrArr[i][j] = tempM.getEntry(i, j) / ((FastMath.exp(Gamma.logGamma(Controls.DEGREE + 1)))
                        * FastMath.pow(dx, Controls.DEGREE));
            }
        }
        tempM = new BlockRealMatrix(tempArrArr);

        //B <- (-1) ^ (deg + 1) * P %*% t(D)
        return (BlockRealMatrix) pM.multiply(tempM.transpose())
                .scalarMultiply(FastMath.pow(-1, (Controls.DEGREE + 1)));
    }
}

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From source file:gamlss.distributions.GT.java

/**
 * Checks whether the nu distribution parameter is valid.
 * @param nu - vector of nu values//from   w  ww  .j  a v  a2  s.  co m
 * @return - - boolean
 */
private boolean isNuValid(final ArrayRealVector nu) {
    return nu.getMinValue() > 0;
}

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From source file:gamlss.distributions.BCPE.java

/**
* Checks whether the mu distribution parameter is valid.
* @param y - vector of response variavbles
* @return - boolean/* www  .  j a v  a 2  s.c om*/
*/
public final boolean isYvalid(final ArrayRealVector y) {
    return y.getMinValue() > 0;
}

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From source file:gamlss.distributions.BCPE.java

/**
* Checks whether the mu distribution parameter is valid.
* @param mu - vector of mu (mean) values
* @return - boolean//from  ww  w  . j a v  a  2 s.  c  o m
*/
private boolean isMuValid(final ArrayRealVector mu) {
    return mu.getMinValue() > 0;
}

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From source file:gamlss.distributions.BCPE.java

/**
 * Checks whether the tau distribution parameter is valid.
 * @param tau - vector of nu values//from   w ww  . j  a v a2  s  .  c o m
 * @return - - boolean
 */
private boolean isTauValid(final ArrayRealVector tau) {
    return tau.getMinValue() > 0;
}

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From source file:gamlss.distributions.BCPE.java

/**
 * Checks whether the sigma distribution parameter is valid.
 * @param sigma - vector of sigma (standard deviation) values
 * @return - - boolean//from   ww w  . j  ava2  s  .c  o m
 */
private boolean isSigmaValid(final ArrayRealVector sigma) {
    return sigma.getMinValue() > 0;
}

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