Remove usages of fabs

src/functions-reference/real-valued_basic_functions.Rmd

@@ -712,13 +712,6 @@ of those types, `abs` returns the same type where each element has had its
 absolute value taken.
 `r since("2.0, vectorized in 2.30")`
 
-<!-- R; fabs; (T x); -->
-\index{{\tt \bfseries fabs }!{\tt (T x): R}|hyperpage}
-
-`R` **`fabs`**`(T x)`<br>\newline
-absolute value of x
-`r since("2.0, vectorized in 2.13, deprecated in 2.30, scheduled for removal in 2.33")`
-
 <!-- real; fdim; (real x, real y); -->
 \index{{\tt \bfseries fdim }!{\tt (real x, real y): real}|hyperpage}
 

src/reference-manual/statements.Rmd

@@ -470,7 +470,7 @@ definitions.  For the case above, the following adjustment will
 account for the log transform.^[Because $\log | \frac{d}{dy} \log y | = \log | 1/y | = - \log |y|$.]
 
 ```stan
-target += - log(fabs(y));
+target += - log(abs(y));
 ```
 
 

src/stan-users-guide/custom-probability.Rmd

@@ -40,15 +40,15 @@ parameters {
   real<lower=-1, upper=1> y;
 }
 model {
-  target += log1m(fabs(y));
+  target += log1m(abs(y));
 }
 ```
 
 The single scalar parameter `y` is declared as lying in the
 interval `(-1,1)`.  The total log probability is
 incremented with the joint log probability of all parameters, i.e.,
 $\log \mathsf{Triangle}(y \mid -1,1)$.  This value is coded in Stan as
-`log1m(fabs(y))`.  The function `log1m` is defined so
+`log1m(abs(y))`.  The function `log1m` is defined so
 that `log1m(x)` has the same value as $\log(1-x)$, but the
 computation is faster, more accurate, and more stable.
 
@@ -64,7 +64,7 @@ $\mathbb{R}$ as follows by defining the probability to be `log(0.0)`,
 i.e., $-\infty$, for values outside of $(-1,1)$.
 
 ```stan
-target += log(fmax(0.0,1 - fabs(y)));
+target += log(fmax(0.0,1 - abs(y)));
 ```
 
 With the constraint on `y` in place, this is just a less
@@ -137,7 +137,7 @@ The following Stan program implements this function,
 ```stan
 real binormal_cdf(real z1, real z2, real rho) {
   if (z1 != 0 || z2 != 0) {
-    real denom = fabs(rho) < 1.0 ? sqrt((1 + rho) * (1 - rho)) 
+    real denom = abs(rho) < 1.0 ? sqrt((1 + rho) * (1 - rho))
                                  : not_a_number();
     real a1 = (z2 / z1 - rho) / denom;
     real a2 = (z1 / z2 - rho) / denom;

src/stan-users-guide/reparameterization.Rmd

@@ -472,7 +472,7 @@ transformed parameters {
   matrix[K, K] J;   // Jacobian matrix of transform
   // ... compute v as a function of u ...
   // ... compute J[m, n] = d.v[m] / d.u[n] ...
-  target += log(fabs(determinant(J)));
+  target += log(abs(determinant(J)));
   // ...
 }
 model {

src/stan-users-guide/simulation-based-calibration.Rmd

@@ -468,10 +468,10 @@ parameters.
 ```stan
 transformed data {
   real mu_sim = normal_rng(0, 5);
-  real tau_sim = fabs(normal_rng(0, 5));
+  real tau_sim = abs(normal_rng(0, 5));
   int<lower=0> J = 8;
   array[J] real theta_sim = normal_rng(rep_vector(mu_sim, J), tau_sim);
-  array[J] real<lower=0> sigma = fabs(normal_rng(rep_vector(0, J), 5));
+  array[J] real<lower=0> sigma = abs(normal_rng(rep_vector(0, J), 5));
   array[J] real y = normal_rng(theta_sim, sigma);
 }
 parameters {

src/stan-users-guide/user-functions.Rmd

@@ -20,8 +20,8 @@ functions {
   real relative_diff(real x, real y) {
     real abs_diff;
     real avg_scale;
-    abs_diff = fabs(x - y);
-    avg_scale = (fabs(x) + fabs(y)) / 2;
+    abs_diff = abs(x - y);
+    avg_scale = (abs(x) + abs(y)) / 2;
     return abs_diff / avg_scale;
   }
 }