update linear interpolation signature

docs/torsten_users_guide.tex

@@ -1082,10 +1082,10 @@ \section{Piecewise linear interpolation}
 \label{sec:org5f1a4b1}
 \index{linear interpolation}
 \begin{minted}[breaklines=true,fontsize=\footnotesize,breakanywhere=true]{stan}
-real linear_interpolation(real xout, array[] real x, array[] real y)
+real pmx_ln_interpolate(real xout, array[] real x, array[] real y)
 \end{minted}
 \begin{minted}[breaklines=true,fontsize=\footnotesize,breakanywhere=true]{stan}
-array[] real linear_interpolation(array[] real xout, array[] real x, array[] real y)
+array[] real pmx_ln_interpolate(array[] real xout, array[] real x, array[] real y)
 \end{minted}
 Torsten also provides function \texttt{linear\_interpolation} for piecewise linear interpolation over a
 set of x, y pairs. It returns the values of a piecewise linear
@@ -1872,7 +1872,7 @@ \section{Linear intepolation}
   for(i in 2:(nx-1))
     x[i] = x[i-1] + xSimplex[i-1] * (xmax - xmin);
 
-  yHat = linear_interpolation(xObs, x, y);
+  yHat = pmx_ln_interpolate(xObs, x, y);
 }
 
 model{
@@ -1885,7 +1885,7 @@ \section{Linear intepolation}
   real yHatPred[nPred];
   real yPred[nPred];
 
-  yHatPred = linear_interpolation(xPred, x, y);
+  yHatPred = pmx_ln_interpolate(xPred, x, y);
   for(i in 1:nPred)
     yPred[i] = normal_rng(yHatPred[i], sigma);
 }

example-models/testInterp2/ln_interpolation.stan

@@ -0,0 +1,46 @@
+data{
+  int nObs;
+  array[nObs] real xObs;
+  array[nObs] real yObs;
+  int nx;
+  int nPred;
+  array[nPred] real xPred;
+}
+
+transformed data{
+  real xmin = min(xObs);
+  real xmax = max(xObs);
+}
+
+parameters{
+  array[nx] real y;
+  real<lower = 0> sigma;
+  simplex[nx - 1] xSimplex;
+}
+
+transformed parameters{
+  array[nObs] real yHat;
+  array[nx] real x;
+
+  x[1] = xmin;
+  x[nx] = xmax;
+  for(i in 2:(nx-1))
+    x[i] = x[i-1] + xSimplex[i-1] * (xmax - xmin);
+
+  yHat = pmx_ln_interpolate(xObs, x, y);
+}
+
+model{
+  xSimplex ~ dirichlet(rep_vector(1, nx - 1));
+  y ~ normal(0, 25);
+  yObs ~ normal(yHat, sigma);
+}
+
+generated quantities{
+  array[nPred] real yHatPred;
+  array[nPred] real yPred;
+
+  yHatPred = pmx_ln_interpolate(xPred, x, y);
+  for(i in 1:nPred)
+    yPred[i] = normal_rng(yHatPred[i], sigma);
+}