1 #ifndef STAN_MATH_REV_MAT_FUN_MULTIPLY_LOWER_TRI_SELF_TRANSPOSE_HPP 2 #define STAN_MATH_REV_MAT_FUN_MULTIPLY_LOWER_TRI_SELF_TRANSPOSE_HPP 28 Knz = (K - J) * J + (J * (J + 1)) / 2;
30 Knz = (K * (K + 1)) / 2;
31 vari** vs =
reinterpret_cast<vari**
>(
34 for (
int m = 0; m < K; ++m)
35 for (
int n = 0; n < ((J < (m + 1)) ? J : (m + 1)); ++n) {
36 vs[pos++] = L(m, n).vi_;
38 for (
int m = 0, mpos = 0; m < K; ++m, mpos += (J < m) ? J : m) {
41 for (
int n = 0, npos = 0; n < m; ++n, npos += (J < n) ? J : n) {
43 vs + mpos, vs + npos, (J < (n + 1)) ? J : (n + 1)));
The variable implementation base class.
static STAN_THREADS_DEF AutodiffStackStorage * instance_
Independent (input) and dependent (output) variables for gradients.
Eigen::Matrix< var, Eigen::Dynamic, Eigen::Dynamic > matrix_v
The type of a matrix holding var values.
Eigen::Matrix< fvar< T >, R, R > multiply_lower_tri_self_transpose(const Eigen::Matrix< fvar< T >, R, C > &m)
void * alloc(size_t len)
Return a newly allocated block of memory of the appropriate size managed by the stack allocator...