static CSSRet ARIMA_CSS(
double[] sy, int[] sarma, TransParsRet trarma, int sncond, boolean giveResid) {
double[] sResid;
double ssq = 0.0;
double[] y = (sy);
double tmp;
double[] phi = (trarma.getsPhi());
double[] theta = (trarma.getsTheta());
double[] w;
double[] resid;
int n = (sy.length);
int[] arma = (sarma);
int p = (trarma.getsPhi().length);
int q = (trarma.getsTheta().length);
int ncond = (sncond);
int l, i, j, ns, nu = 0;
boolean useResid = (giveResid);
w = new double[n];
for (l = 0; l < n; l++) w[l] = y[l];
for (i = 0; i < arma[5]; i++) for (l = n - 1; l > 0; l--) w[l] -= w[l - 1];
ns = arma[4];
for (i = 0; i < arma[6]; i++) for (l = n - 1; l >= ns; l--) w[l] -= w[l - ns];
sResid = new double[n];
resid = (sResid);
if (useResid) for (l = 0; l < ncond && l < n; l++) resid[l] = 0;
for (l = ncond; l < n; l++) {
tmp = w[l];
for (j = 0; j < p; j++) tmp -= phi[j] * w[l - j - 1];
for (j = 0; j < Math.min(l - ncond, q); j++) tmp -= theta[j] * resid[l - j - 1];
resid[l] = tmp;
if (!Double.isNaN(tmp)) {
nu++;
ssq += tmp * tmp;
}
}
CSSRet res = new CSSRet();
res.setUseResid(useResid);
if (useResid) {
res.setValue(ssq / nu);
res.setsResid(sResid);
return res;
} else {
res.setValue(ssq / nu);
}
return res;
}
private ARIMARet arima() {
double[] x = analyticData;
int[] order = new int[] {p, d, q};
int[] seasonalOrder = new int[] {0, 0, 0};
int seasonalPeriod = 1;
int n = x.length;
arma =
new int[] {
order[0],
order[2],
seasonalOrder[0],
seasonalOrder[2],
seasonalPeriod,
order[1],
seasonalOrder[1]
};
int narma = 0;
for (int i = 0; i < 4; i++) {
narma += arma[i];
}
double[] delta = new double[1];
delta[0] = 1;
double[] tmp = new double[] {1, -1};
for (int i = 0; i < order[1]; i++) {
delta = TSconv(delta, tmp);
}
tmp = new double[2 + seasonalPeriod - 1];
tmp[0] = 1;
tmp[tmp.length - 1] = -1;
for (int i = 0; i < seasonalPeriod - 1; i++) {
tmp[i] = 0;
}
for (int i = 0; i < seasonalOrder[1]; i++) {
delta = TSconv(delta, tmp);
}
double[] deltaOld = delta;
delta = new double[deltaOld.length - 1];
for (int i = 0; i < delta.length; i++) {
delta[i] = -deltaOld[i + 1];
}
int nUsed = n;
nUsed = n - delta.length;
int nd = order[1] + seasonalOrder[1];
ncxreg = 0;
boolean includeMean = true; // false;
double[] xreg = null;
if (includeMean && (nd == 0)) {
xreg = new double[n];
for (int i = 0; i < n; i++) {
xreg[i] = 1;
}
ncxreg = ncxreg + 1;
}
int ncond = order[1] + seasonalOrder[1] * seasonalPeriod;
int ncond1 = order[0] + seasonalPeriod * seasonalOrder[0];
Integer nCond = null;
if (nCond != null) ncond = ncond + Math.max(nCond, ncond1);
else ncond = ncond + ncond1;
double[] fixed = new double[narma + ncxreg];
for (int i = 0; i < fixed.length; i++) {
fixed[i] = Double.NaN;
}
boolean[] mask = new boolean[fixed.length];
for (int i = 0; i < mask.length; i++) {
if (Double.isNaN(fixed[i])) {
mask[i] = true;
} else {
mask[i] = false;
}
}
boolean noOptim = false;
double[] init0 = new double[narma];
double[] parscale = new double[narma];
for (int i = 0; i < parscale.length; i++) {
parscale[i] = 1;
}
if (ncxreg != 0) {
double[][] lmxreg = new double[1][];
lmxreg[0] = new double[xreg.length];
for (int i = 0; i < lmxreg[0].length; i++) {
lmxreg[0][i] = xreg[i];
}
int lmp = lmxreg.length;
double[][] lmy = new double[1][];
lmy[0] = new double[x.length];
System.arraycopy(x, 0, lmy[0], 0, lmy[0].length);
int lmny = lmy.length;
double[][] work = new double[2][lmp];
double[][] b = new double[lmny][lmp];
double[][] residuals = new double[lmy.length][lmy[0].length];
double[][] effects = new double[lmy.length][lmy[0].length];
double[] qraux = new double[lmp];
for (int i = 0; i < lmy.length; i++) {
System.arraycopy(lmy[i], 0, residuals[i], 0, residuals[i].length);
System.arraycopy(lmy[i], 0, effects[i], 0, effects[i].length);
}
int[] jpvt = new int[lmp];
for (int i = 0; i < jpvt.length; i++) {
jpvt[i] = i + 1;
}
LMRet lmRet =
LM.dqrls(lmxreg, n, 1, lmy, 1, 1e-07, b, residuals, effects, 1, jpvt, qraux, work);
// n.used <- sum(!is.na(resid(fit))) - length(Delta)
double coefFit = lmRet.getCoefficient()[0];
double[] init0New = new double[init0.length + 1];
System.arraycopy(init0, 0, init0New, 0, init0.length);
init0New[init0.length] = coefFit;
init0 = init0New;
double ses = lmRet.getSes()[0];
double[] parscaleNew = new double[parscale.length + 1];
System.arraycopy(parscale, 0, parscaleNew, 0, parscale.length);
parscaleNew[parscale.length] = 10 * ses;
parscale = parscaleNew;
}
double[] init = init0;
double[] coef = fixed;
XReg xReg = new XReg();
xReg.setNcxreg(ncxreg);
xReg.setNarma(narma);
xReg.setXreg(xreg);
if (ncond >= n) {
// TODO
// throw new WrongUsedException(this,AlpineAnalysisErrorName.DATASET_TOO_SMALL);
}
OptimResHessRet res = Optimization.optim(init, arma, ncond, true, x, xReg, parscale);
coef = res.getRes().getPar();
TransParsRet trarma = ARIMA_transPars(coef, arma, false);
double kappa = 1e6;
MakeARIMARet mod = makeARIMA(coef, trarma.getsPhi(), trarma.getsTheta(), delta, kappa);
if (ncxreg > 0) {
for (int i = 0; i < x.length; i++) {
x[i] = x[i] - xreg[i] * coef[narma];
}
}
double[] P = new double[mod.getP().length * mod.getP()[0].length];
for (int i = 0; i < mod.getP().length; i++) {
for (int j = 0; j < mod.getP()[0].length; j++) {
P[i * mod.getP()[0].length + j] = mod.getP()[i][j];
}
}
double[] Pn = new double[mod.getPn().length * mod.getPn()[0].length];
for (int i = 0; i < mod.getPn().length; i++) {
for (int j = 0; j < mod.getPn()[0].length; j++) {
Pn[i * mod.getPn()[0].length + j] = mod.getPn()[i][j];
}
}
ARIMA_Like(x, mod.getPhi(), mod.getTheta(), mod.getDelta(), mod.getA(), P, Pn, 0, true);
CSSRet val = ARIMA_CSS(x, arma, trarma, ncond, true);
sigma2 = val.getValue();
Matrix var = null;
if (noOptim) {
// var = 0;
} else {
// try {
try {
var = res.getHess().times(nUsed).SVDInverse();
} catch (Exception e) {
// TODO Auto-generated catch block
return null;
// e.printStackTrace();
}
// } catch (OperatorException e) {
// logger.error("svd exception:"+e.getLocalizedMessage()); //TODO
// }
}
double[] varCoef = new double[coef.length];
String varString = new String();
if (var != null) {
for (int i = 0; i < var.getColumnDimension(); i++) {
varCoef[i] = Math.sqrt(var.get(i, i));
varString += "," + varCoef[i];
}
}
double value = 2 * nUsed * res.getRes().getValue() + nUsed + nUsed * Math.log(2 * Math.PI);
double aic = Double.NaN;
ARIMARet aRIMARes = new ARIMARet();
aRIMARes.setCoef(coef);
aRIMARes.setSigma2(sigma2);
aRIMARes.setLoglik(-0.5 * value);
likelihood = aRIMARes.getLoglik();
aRIMARes.setAic(aic);
aRIMARes.setArma(arma);
aRIMARes.setX(x);
aRIMARes.setnCond(ncond);
aRIMARes.setModel(mod);
aRIMARes.setVarCoef(varCoef);
aRIMARes.setResiduals(val.getsResid());
return aRIMARes;
}
