function secondordercalibration($X, $Y, $ConfidenceInterval)
{
$numX = count($X);
$numY = count($Y);
if ($numX != $numY) {
die("Error: Size of X and Y vectors must be the same.");
}
if ($numX <= 1) {
die("Error: Size of input array must be at least 2.");
}
//General parameters
$this->n = $numX;
$this->X = $X;
$this->Y = $Y;
//second-order parameters
$this->XMean = $this->getMean($this->X);
$this->YMean = $this->getMean($this->Y);
$this->SumXX = $this->getSumXX();
$this->SumX2Y = $this->getSumX2Y();
$this->SumXY = $this->getSumXY();
$this->SumX4 = $this->getSumX4();
$this->SumX3 = $this->getSumX3();
$this->SumX2 = $this->getSumX2();
$this->SumX = $this->getSumX();
$this->SumY = $this->getSumY();
$this->Den = $this->getDen();
$this->SOc = $this->getSOc();
//Second order c parameter.
$this->SOb = $this->getSOb();
//Second order b parameter.
$this->SOa = $this->getSOa();
//Second order a parameter.
$this->Slope = $this->getSlope();
$this->PredictedY = $this->getPredictedY();
$this->Error = $this->getError();
$this->SquaredError = $this->getSquaredError();
$this->SumError = $this->getSumError();
$this->SumSquaredError = $this->getSumSquaredError();
$this->ErrorVariance = $this->getErrorVariance();
$this->StdErr = $this->getStdErr();
$this->RStdErr = $this->getRStdErr();
$this->RStdErr100 = $this->getRStdErr100();
$this->Infpoint = $this->getInfpoint();
$this->SumYY = $this->getSumYY();
$this->RSquared = $this->getRSquared();
$this->CCalfa = $this->getCCalfa();
$this->CCbeta = $this->getCCbeta();
$this->ConfInt = $ConfidenceInterval;
$this->Alpha = (100 - $this->ConfInt) / 100;
$this->Delta = 2 * (100 - $this->ConfInt) / 100;
//One tail aproximation according to ISO 11843-2
//Probability parameters
$dist = new SchemA();
$this->AlphaTVal = $dist->getInverseStudentT($this->Alpha, $this->X);
$this->DeltaTVal = $dist->getInverseStudentT($this->Delta, $this->X);
return true;
}
function linearcalibration($X, $Y, $ConfidenceInterval, $W)
{
$numX = count($X);
$numY = count($Y);
if ($numX != $numY) {
die("Error: Size of X and Y vectors must be the same.");
}
if ($numX <= 1) {
die("Error: Size of input array must be at least 2.");
}
//General parameters
$this->n = $numX;
$this->X = $X;
$this->Y = $Y;
$this->W = $W;
//Confidence interval
$this->ConfInt = $ConfidenceInterval;
$this->Alpha = (100 - $this->ConfInt) / 100;
$this->Delta = 2 * (100 - $this->ConfInt) / 100;
//One tail aproximation according to ISO 11843-2
//Linear parameters
$this->XMean = $this->getMean($this->X);
$this->YMean = $this->getMean($this->Y);
$this->SumXX = $this->getSumXX();
$this->SumYY = $this->getSumYY();
$this->SumXY = $this->getSumXY();
$this->Slope = $this->getSlope();
$this->YInt = $this->getYInt();
$this->PredictedY = $this->getPredictedY();
$this->Error = $this->getError();
$this->SquaredError = $this->getSquaredError();
$this->SumError = $this->getSumError();
$this->SumSquaredError = $this->getSumSquaredError();
$this->ErrorVariance = $this->getErrorVariance();
$this->StdErr = $this->getStdErr();
$this->RStdErr = $this->getRStdErr();
$this->RStdErr100 = $this->getRStdErr100();
$this->RSDErrFR = $this->getRSDErrFR();
$this->SlopeStdErr = $this->getSlopeStdErr();
$this->YIntStdErr = $this->getYIntStdErr();
$this->SlopeTVal = $this->getSlopeTVal();
$this->YIntTVal = $this->getYIntTVal();
$this->R = $this->getR();
$this->RSquared = $this->getRSquared();
$this->DF = $this->getDF();
$this->CCalfa = $this->getCCalfa();
$this->CCbeta = $this->getCCbeta();
$this->ConfIntOfSlope = $this->getConfIntOfSlope();
//Weight parameters
$this->SumW = $this->getSumW();
$this->SumWX = $this->getSumWX();
$this->SumWXX = $this->getSumWXX();
$this->SumWYY = $this->getSumWYY();
$this->SumWX2 = $this->getSumWX2();
$this->SumWY2 = $this->getSumWY2();
$this->SumWY = $this->getSumWY();
$this->SumWXY = $this->getSumWXY();
$this->SlopeW = $this->getSlopeW();
$this->YIntW = $this->getYIntW();
$this->RW = $this->getRW();
$this->RSquaredW = $this->getRSquaredW();
$this->PredictedYW = $this->getPredictedYW();
$this->ErrorW = $this->getErrorW();
$this->SquaredErrorW = $this->getSquaredErrorW();
$this->SumErrorW = $this->getSumErrorW();
$this->SumSquaredErrorW = $this->getSumSquaredErrorW();
$this->ErrorVarianceW = $this->getErrorVarianceW();
$this->StdErrW = $this->getStdErrW();
$this->RStdErrW = $this->getRStdErrW();
$this->RStdErrW100 = $this->getRStdErrW100();
$this->CCalfaW = $this->getCCalfaW();
$this->CCbetaW = $this->getCCbetaW();
//Probability parameters
$dist = new SchemA();
$this->SlopeProb = $dist->getStudentT($this->SlopeTVal, $this->DF);
$this->YIntProb = $dist->getStudentT($this->YIntTVal, $this->DF);
$this->AlphaTVal = $dist->getInverseStudentT($this->Alpha, $this->X);
$this->DeltaTVal = $dist->getInverseStudentT($this->Delta, $this->X);
return true;
}