double regression(int Nind, int Nmark, cvector cofactor, MQMMarkerMatrix marker, vector y,
vector *weight, ivector ind, int Naug, double *variance,
vector Fy, bool biasadj, bool fitQTL, bool dominance, bool verbose) {
debug_trace("regression IN\n");
/*
cofactor[j] at locus j:
MNOCOF: no cofactor at locus j
MCOF: cofactor at locus j
MSEX: QTL at locus j, but QTL effect is not included in the model
MQTL: QTL at locu j and QTL effect is included in the model
*/
//Calculate the dimensions of the designMatrix
int dimx=designmatrixdimensions(cofactor,Nmark,dominance);
int j, jj;
const int dimx_alloc = dimx+2;
//Allocate structures
matrix XtWX = newmatrix(dimx_alloc, dimx_alloc);
cmatrix Xt = newcmatrix(dimx_alloc, Naug);
vector XtWY = newvector(dimx_alloc);
//Reset dimension designmatrix
dimx = 1;
for (j=0; j<Nmark; j++){
if ((cofactor[j]==MCOF)||(cofactor[j]==MQTL)) dimx+= (dominance ? 2 : 1);
}
cvector xtQTL = newcvector(dimx);
int jx=0;
for (int i=0; i<Naug; i++) Xt[jx][i]= MH;
xtQTL[jx]= MNOCOF;
for (j=0; j<Nmark; j++)
if (cofactor[j]==MCOF) { // cofactor (not a QTL moving along the chromosome)
jx++;
xtQTL[jx]= MCOF;
if (dominance) {
for (int i=0; i<Naug; i++)
if (marker[j][i]==MH) {
Xt[jx][i]=48; //ASCII code 47, 48 en 49 voor -1, 0, 1;
Xt[jx+1][i]=49;
} else if (marker[j][i]==MAA) {
Xt[jx][i]=47; // '/' stands for -1
Xt[jx+1][i]=48;
} else {
Xt[jx][i]=49;
Xt[jx+1][i]=48;
}
jx++;
xtQTL[jx]= MCOF;
} else {
for (int i=0; i<Naug; i++) {
if (marker[j][i]==MH) {
Xt[jx][i]=48; //ASCII code 47, 48 en 49 voor -1, 0, 1;
} else if (marker[j][i]==MAA) {
Xt[jx][i]=47; // '/' stands for -1
} else {
Xt[jx][i]=49;
}
}
}
} else if (cofactor[j]==MQTL) { // QTL
jx++;
xtQTL[jx]= MSEX;
if (dominance) {
jx++;
xtQTL[jx]= MQTL;
}
}
//Rprintf("calculate xtwx and xtwy\n");
/* calculate xtwx and xtwy */
double xtwj, yi, wi, calc_i;
for (j=0; j<dimx; j++) {
XtWY[j]= 0.0;
for (jj=0; jj<dimx; jj++) XtWX[j][jj]= 0.0;
}
if (!fitQTL){
for (int i=0; i<Naug; i++) {
yi= y[i];
wi= (*weight)[i];
//in the original version when we enable Dominance , we crash around here
for (j=0; j<dimx; j++) {
xtwj= ((double)Xt[j][i]-48.0)*wi;
XtWY[j]+= xtwj*yi;
for (jj=0; jj<=j; jj++) XtWX[j][jj]+= xtwj*((double)Xt[jj][i]-48.0);
}
}
}else{ // QTL is moving along the chromosomes
for (int i=0; i<Naug; i++) {
wi= (*weight)[i]+ (*weight)[i+Naug]+ (*weight)[i+2*Naug];
yi= y[i];
//Changed <= to < to prevent chrashes, this could make calculations a tad different then before
for (j=0; j<dimx; j++){
if (xtQTL[j]<=MCOF) {
xtwj= ((double)Xt[j][i]-48.0)*wi;
XtWY[j]+= xtwj*yi;
for (jj=0; jj<=j; jj++)
if (xtQTL[jj]<=MCOF) XtWX[j][jj]+= xtwj*((double)Xt[jj][i]-48.0);
else if (xtQTL[jj]==MSEX) // QTL: additive effect if QTL=MCOF or MSEX
{ // QTL==MAA
XtWX[j][jj]+= ((double)(Xt[j][i]-48.0))*(*weight)[i]*(47.0-48.0);
// QTL==MBB
XtWX[j][jj]+= ((double)(Xt[j][i]-48.0))*(*weight)[i+2*Naug]*(49.0-48.0);
} else // (xtQTL[jj]==MNOTAA) QTL: dominance effect only if QTL=MCOF
{ // QTL==MH
XtWX[j][jj]+= ((double)(Xt[j][i]-48.0))*(*weight)[i+Naug]*(49.0-48.0);
}
} else if (xtQTL[j]==MSEX) { // QTL: additive effect if QTL=MCOF or MSEX
xtwj= -1.0*(*weight)[i]; // QTL==MAA
XtWY[j]+= xtwj*yi;
for (jj=0; jj<j; jj++) XtWX[j][jj]+= xtwj*((double)Xt[jj][i]-48.0);
XtWX[j][j]+= xtwj*-1.0;
xtwj= 1.0*(*weight)[i+2*Naug]; // QTL==MBB
XtWY[j]+= xtwj*yi;
for (jj=0; jj<j; jj++) XtWX[j][jj]+= xtwj*((double)Xt[jj][i]-48.0);
XtWX[j][j]+= xtwj*1.0;
} else { // (xtQTL[j]==MQTL) QTL: dominance effect only if QTL=MCOF
xtwj= 1.0*(*weight)[i+Naug]; // QTL==MCOF
XtWY[j]+= xtwj*yi;
// j-1 is for additive effect, which is orthogonal to dominance effect
for (jj=0; jj<j-1; jj++) XtWX[j][jj]+= xtwj*((double)Xt[jj][i]-48.0);
XtWX[j][j]+= xtwj*1.0;
}
}
}
}
for (j=0; j<dimx; j++){
for (jj=j+1; jj<dimx; jj++){
XtWX[j][jj]= XtWX[jj][j];
}
}
int d;
ivector indx= newivector(dimx);
/* solve equations */
ludcmp(XtWX, dimx, indx, &d);
lusolve(XtWX, dimx, indx, XtWY);
double* indL = (double *)R_alloc(Nind, sizeof(double));
int newNaug = ((!fitQTL) ? Naug : 3*Naug);
vector fit = newvector(newNaug);
vector resi = newvector(newNaug);
debug_trace("Calculate residuals\n");
if (*variance<0) {
*variance= 0.0;
if (!fitQTL)
for (int i=0; i<Naug; i++) {
fit[i]= 0.0;
for (j=0; j<dimx; j++)
fit[i]+=((double)Xt[j][i]-48.0)*XtWY[j];
resi[i]= y[i]-fit[i];
*variance += (*weight)[i]*pow(resi[i], 2.0);
}
else
for (int i=0; i<Naug; i++) {
fit[i]= 0.0;
fit[i+Naug]= 0.0;
fit[i+2*Naug]= 0.0;
for (j=0; j<dimx; j++)
if (xtQTL[j]<=MCOF) {
calc_i =((double)Xt[j][i]-48.0)*XtWY[j];
fit[i]+= calc_i;
fit[i+Naug]+= calc_i;
fit[i+2*Naug]+= calc_i;
} else if (xtQTL[j]==MSEX) {
fit[i]+=-1.0*XtWY[j];
fit[i+2*Naug]+=1.0*XtWY[j];
} else
fit[i+Naug]+=1.0*XtWY[j];
resi[i]= y[i]-fit[i];
resi[i+Naug]= y[i]-fit[i+Naug];
resi[i+2*Naug]= y[i]-fit[i+2*Naug];
*variance +=(*weight)[i]*pow(resi[i], 2.0);
*variance +=(*weight)[i+Naug]*pow(resi[i+Naug], 2.0);
*variance +=(*weight)[i+2*Naug]*pow(resi[i+2*Naug], 2.0);
}
*variance/= (!biasadj ? Nind : Nind-dimx); // to compare results with Johan; variance/=Nind;
if (!fitQTL)
for (int i=0; i<Naug; i++) Fy[i]= Lnormal(resi[i], *variance);
else
for (int i=0; i<Naug; i++) {
Fy[i] = Lnormal(resi[i], *variance);
Fy[i+Naug] = Lnormal(resi[i+Naug], *variance);
Fy[i+2*Naug]= Lnormal(resi[i+2*Naug], *variance);
}
} else {
if (!fitQTL)
for (int i=0; i<Naug; i++) {
fit[i]= 0.0;
for (j=0; j<dimx; j++)
fit[i]+=((double)Xt[j][i]-48.0)*XtWY[j];
resi[i]= y[i]-fit[i];
Fy[i] = Lnormal(resi[i], *variance); // ????
}
else
for (int i=0; i<Naug; i++) {
fit[i]= 0.0;
fit[i+Naug]= 0.0;
fit[i+2*Naug]= 0.0;
for (j=0; j<dimx; j++)
if (xtQTL[j]<=MCOF) {
calc_i =((double)Xt[j][i]-48.0)*XtWY[j];
fit[i]+= calc_i;
fit[i+Naug]+= calc_i;
fit[i+2*Naug]+= calc_i;
} else if (xtQTL[j]==MSEX) {
fit[i]+=-1.0*XtWY[j];
fit[i+2*Naug]+=1.0*XtWY[j];
} else
fit[i+Naug]+=1.0*XtWY[j];
resi[i]= y[i]-fit[i];
resi[i+Naug]= y[i]-fit[i+Naug];
resi[i+2*Naug]= y[i]-fit[i+2*Naug];
Fy[i] = Lnormal(resi[i], *variance);
Fy[i+Naug] = Lnormal(resi[i+Naug], *variance);
Fy[i+2*Naug]= Lnormal(resi[i+2*Naug], *variance);
}
}
/* calculation of logL */
debug_trace("calculate logL\n");
double logL=0.0;
for (int i=0; i<Nind; i++) {
indL[i]= 0.0;
}
if (!fitQTL) {
for (int i=0; i<Naug; i++) indL[ind[i]]+=(*weight)[i]*Fy[i];
} else {
for (int i=0; i<Naug; i++) {
indL[ind[i]]+=(*weight)[i]* Fy[i];
indL[ind[i]]+=(*weight)[i+Naug]* Fy[i+Naug];
indL[ind[i]]+=(*weight)[i+2*Naug]*Fy[i+2*Naug];
}
}
for (int i=0; i<Nind; i++) { //Sum up log likelihoods for each individual
logL+= log(indL[i]);
}
return (double)logL;
}
double multivariateregression(uint nvariables, uint nsamples, dmatrix x, dvector w, dvector y, dvector Fy){
int d=0;
double xtwj;
dmatrix Xt = newdmatrix(nvariables,nsamples);
dmatrix XtWX = newdmatrix(nvariables, nvariables);
dvector XtWY = newdvector(nvariables);
ivector indx = newivector(nvariables);
//cout << "calculating Xt" << endl;
for(uint i=0; i<nsamples; i++){
for(uint j=0; j<nvariables; j++){
Xt[j][i] = x[i][j];
}
}
//cout << "calculating XtWX and XtWY" << endl;
for(uint i=0; i<nsamples; i++){
for(uint j=0; j<nvariables; j++){
xtwj = Xt[j][i] * w[i];
XtWY[j] += xtwj * y[i];
for(uint jj=0; jj<=j; jj++){
XtWX[j][jj] += xtwj * Xt[jj][i];
}
}
}
LUdecomposition(XtWX, nvariables, indx, &d);
LUsolve(XtWX, nvariables, indx, XtWY);
//cout << "Estimated parameters:" << endl;
//for (uint i=0; i < nvariables; i++){
// cout << "Parameter " << i << " = " << XtWY[i] << endl;
//}
dvector fit = newdvector(nsamples);
dvector residual = newdvector(nsamples);
dvector indL = newdvector(nsamples);
double variance= 0.0;
double logL=0.0;
for (uint i=0; i<nsamples; i++){
fit[i]= 0.0;
for (uint j=0; j<nvariables; j++){
fit[i] += Xt[j][i] * XtWY[j];
residual[i] = y[i]-fit[i];
variance += w[i]*pow(residual[i],2.0);
}
Fy[i] = Lnormal(residual[i],variance);
indL[i] += w[i]*Fy[i];
logL += log(indL[i]);
}
//cout << "Estimated response:" << endl;
//printdvector(fit,nsamples);
//cout << "Residuals:" << endl;
//printdvector(residual,nsamples);
//cout << "Estimated Fy:" << endl;
//printdvector(Fy,nsamples);
//cout << "Variance: " << variance << endl;
//cout << "Loglikelihood: " << logL << endl;
freematrix((void**)Xt,nvariables);
freematrix((void**)XtWX, nvariables);
freevector((void*)XtWY);
freevector((void*)fit);
freevector((void*)residual);
freevector((void*)indL);
return logL;
}
