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Merge pull request #3101 from stan-dev/sum-to-zero-constraint-ilr
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Add sum_to_zero constraint, free, and check based on ILR transform
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WardBrian authored Aug 7, 2024
2 parents f120c5e + 5ae902d commit 9b1f08b
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2 changes: 2 additions & 0 deletions stan/math/prim/constraint.hpp
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#include <stan/math/prim/constraint/stochastic_column_free.hpp>
#include <stan/math/prim/constraint/stochastic_row_constrain.hpp>
#include <stan/math/prim/constraint/stochastic_row_free.hpp>
#include <stan/math/prim/constraint/sum_to_zero_constrain.hpp>
#include <stan/math/prim/constraint/sum_to_zero_free.hpp>
#include <stan/math/prim/constraint/ub_constrain.hpp>
#include <stan/math/prim/constraint/ub_free.hpp>
#include <stan/math/prim/constraint/unit_vector_constrain.hpp>
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166 changes: 166 additions & 0 deletions stan/math/prim/constraint/sum_to_zero_constrain.hpp
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#ifndef STAN_MATH_PRIM_CONSTRAINT_SUM_TO_ZERO_CONSTRAIN_HPP
#define STAN_MATH_PRIM_CONSTRAINT_SUM_TO_ZERO_CONSTRAIN_HPP

#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/fun/Eigen.hpp>
#include <stan/math/prim/fun/to_ref.hpp>
#include <stan/math/prim/fun/inv_sqrt.hpp>
#include <stan/math/prim/functor/apply_vector_unary.hpp>
#include <cmath>

namespace stan {
namespace math {

/**
* Return a vector with sum zero corresponding to the specified
* free vector.
*
* The sum-to-zero transform is defined using a modified version of the
* the inverse of the isometric log ratio transform (ILR).
* See:
* Egozcue, Juan Jose; Pawlowsky-Glahn, Vera; Mateu-Figueras, Gloria;
* Barcelo-Vidal, Carles (2003), "Isometric logratio transformations for
* compositional data analysis", Mathematical Geology, 35 (3): 279–300,
* doi:10.1023/A:1023818214614, S2CID 122844634
*
* This implementation is closer to the description of the same using "pivot
* coordinates" in
* Filzmoser, P., Hron, K., Templ, M. (2018). Geometrical Properties of
* Compositional Data. In: Applied Compositional Data Analysis. Springer Series
* in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-96422-5_3
*
* This is a linear transform, with no Jacobian.
*
* @tparam Vec type of the vector
* @param y Free vector input of dimensionality K - 1.
* @return Zero-sum vector of dimensionality K.
*/
template <typename Vec, require_eigen_col_vector_t<Vec>* = nullptr,
require_not_st_var<Vec>* = nullptr>
inline plain_type_t<Vec> sum_to_zero_constrain(const Vec& y) {
const auto N = y.size();

plain_type_t<Vec> z = Eigen::VectorXd::Zero(N + 1);
if (unlikely(N == 0)) {
return z;
}

auto&& y_ref = to_ref(y);

value_type_t<Vec> sum_w(0);
for (int i = N; i > 0; --i) {
double n = static_cast<double>(i);
auto w = y_ref(i - 1) * inv_sqrt(n * (n + 1));
sum_w += w;

z.coeffRef(i - 1) += sum_w;
z.coeffRef(i) -= w * n;
}

return z;
}

/**
* Return a vector with sum zero corresponding to the specified
* free vector.
*
* The sum-to-zero transform is defined using a modified version of the
* the inverse of the isometric log ratio transform (ILR).
* See:
* Egozcue, Juan Jose; Pawlowsky-Glahn, Vera; Mateu-Figueras, Gloria;
* Barcelo-Vidal, Carles (2003), "Isometric logratio transformations for
* compositional data analysis", Mathematical Geology, 35 (3): 279–300,
* doi:10.1023/A:1023818214614, S2CID 122844634
*
* This implementation is closer to the description of the same using "pivot
* coordinates" in
* Filzmoser, P., Hron, K., Templ, M. (2018). Geometrical Properties of
* Compositional Data. In: Applied Compositional Data Analysis. Springer Series
* in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-96422-5_3
*
* This is a linear transform, with no Jacobian.
*
* @tparam Vec type of the vector
* @param y Free vector input of dimensionality K - 1.
* @param lp unused
* @return Zero-sum vector of dimensionality K.
*/
template <typename Vec, require_eigen_col_vector_t<Vec>* = nullptr,
require_not_st_var<Vec>* = nullptr>
inline plain_type_t<Vec> sum_to_zero_constrain(const Vec& y,
value_type_t<Vec>& lp) {
return sum_to_zero_constrain(y);
}

/**
* Return a vector with sum zero corresponding to the specified
* free vector.
*
* The sum-to-zero transform is defined using a modified version of
* the inverse of the isometric log ratio transform (ILR).
* See:
* Egozcue, Juan Jose; Pawlowsky-Glahn, Vera; Mateu-Figueras, Gloria;
* Barcelo-Vidal, Carles (2003), "Isometric logratio transformations for
* compositional data analysis", Mathematical Geology, 35 (3): 279–300,
* doi:10.1023/A:1023818214614, S2CID 122844634
*
* This implementation is closer to the description of the same using "pivot
* coordinates" in
* Filzmoser, P., Hron, K., Templ, M. (2018). Geometrical Properties of
* Compositional Data. In: Applied Compositional Data Analysis. Springer Series
* in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-96422-5_3
*
* This is a linear transform, with no Jacobian.
*
* @tparam Jacobian unused
* @tparam Vec A type inheriting from `Eigen::DenseBase` or a `var_value` with
* inner type inheriting from `Eigen::DenseBase` with compile time dynamic rows
* and 1 column
* @param[in] y free vector
* @param[in, out] lp unused
* @return Zero-sum vector of dimensionality one greater than `y`
*/
template <bool Jacobian, typename Vec, require_not_std_vector_t<Vec>* = nullptr>
inline plain_type_t<Vec> sum_to_zero_constrain(const Vec& y,
return_type_t<Vec>& lp) {
return sum_to_zero_constrain(y);
}

/**
* Return a vector with sum zero corresponding to the specified
* free vector.
*
* The sum-to-zero transform is defined using a modified version of
* the inverse of the isometric log ratio transform (ILR).
* See:
* Egozcue, Juan Jose; Pawlowsky-Glahn, Vera; Mateu-Figueras, Gloria;
* Barcelo-Vidal, Carles (2003), "Isometric logratio transformations for
* compositional data analysis", Mathematical Geology, 35 (3): 279–300,
* doi:10.1023/A:1023818214614, S2CID 122844634
*
* This implementation is closer to the description of the same using "pivot
* coordinates" in
* Filzmoser, P., Hron, K., Templ, M. (2018). Geometrical Properties of
* Compositional Data. In: Applied Compositional Data Analysis. Springer Series
* in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-96422-5_3
*
* This is a linear transform, with no Jacobian.
*
* @tparam Jacobian unused
* @tparam Vec A standard vector with inner type inheriting from
* `Eigen::DenseBase` or a `var_value` with inner type inheriting from
* `Eigen::DenseBase` with compile time dynamic rows and 1 column
* @param[in] y free vector
* @param[in, out] lp unused
* @return Zero-sum vectors of dimensionality one greater than `y`
*/
template <bool Jacobian, typename T, require_std_vector_t<T>* = nullptr>
inline auto sum_to_zero_constrain(const T& y, return_type_t<T>& lp) {
return apply_vector_unary<T>::apply(
y, [](auto&& v) { return sum_to_zero_constrain(v); });
}

} // namespace math
} // namespace stan

#endif
80 changes: 80 additions & 0 deletions stan/math/prim/constraint/sum_to_zero_free.hpp
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#ifndef STAN_MATH_PRIM_CONSTRAINT_SUM_TO_ZERO_FREE_HPP
#define STAN_MATH_PRIM_CONSTRAINT_SUM_TO_ZERO_FREE_HPP

#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err.hpp>
#include <stan/math/prim/fun/Eigen.hpp>
#include <stan/math/prim/fun/to_ref.hpp>
#include <stan/math/prim/fun/sqrt.hpp>
#include <stan/math/prim/functor/apply_vector_unary.hpp>
#include <cmath>

namespace stan {
namespace math {

/**
* Return an unconstrained vector.
*
* The sum-to-zero transform is defined using a modified version of the
* isometric log ratio transform (ILR).
* See:
* Egozcue, Juan Jose; Pawlowsky-Glahn, Vera; Mateu-Figueras, Gloria;
* Barcelo-Vidal, Carles (2003), "Isometric logratio transformations for
* compositional data analysis", Mathematical Geology, 35 (3): 279–300,
* doi:10.1023/A:1023818214614, S2CID 122844634
*
* This implementation is closer to the description of the same using "pivot
* coordinates" in
* Filzmoser, P., Hron, K., Templ, M. (2018). Geometrical Properties of
* Compositional Data. In: Applied Compositional Data Analysis. Springer Series
* in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-319-96422-5_3
*
* @tparam ColVec a column vector type
* @param z Vector of length K.
* @return Free vector of length (K-1).
* @throw std::domain_error if z does not sum to zero
*/
template <typename Vec, require_eigen_vector_t<Vec>* = nullptr>
inline plain_type_t<Vec> sum_to_zero_free(const Vec& z) {
const auto& z_ref = to_ref(z);
check_sum_to_zero("stan::math::sum_to_zero_free", "sum_to_zero variable",
z_ref);

const auto N = z.size() - 1;

plain_type_t<Vec> y = Eigen::VectorXd::Zero(N);
if (unlikely(N == 0)) {
return y;
}

y.coeffRef(N - 1) = -z_ref(N) * sqrt(N * (N + 1)) / N;

value_type_t<Vec> sum_w(0);

for (int i = N - 2; i >= 0; --i) {
double n = static_cast<double>(i + 1);
auto w = y(i + 1) / sqrt((n + 1) * (n + 2));
sum_w += w;
y.coeffRef(i) = (sum_w - z_ref(i + 1)) * sqrt(n * (n + 1)) / n;
}

return y;
}

/**
* Overload of `sum_to_zero_free()` to untransform each Eigen vector
* in a standard vector.
* @tparam T A standard vector with with a `value_type` which inherits from
* `Eigen::MatrixBase` with compile time rows or columns equal to 1.
* @param z The standard vector to untransform.
*/
template <typename T, require_std_vector_t<T>* = nullptr>
auto sum_to_zero_free(const T& z) {
return apply_vector_unary<T>::apply(
z, [](auto&& v) { return sum_to_zero_free(v); });
}

} // namespace math
} // namespace stan

#endif
1 change: 1 addition & 0 deletions stan/math/prim/err.hpp
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#include <stan/math/prim/err/check_std_vector_index.hpp>
#include <stan/math/prim/err/check_stochastic_column.hpp>
#include <stan/math/prim/err/check_stochastic_row.hpp>
#include <stan/math/prim/err/check_sum_to_zero.hpp>
#include <stan/math/prim/err/check_symmetric.hpp>
#include <stan/math/prim/err/check_unit_vector.hpp>
#include <stan/math/prim/err/check_vector.hpp>
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72 changes: 72 additions & 0 deletions stan/math/prim/err/check_sum_to_zero.hpp
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#ifndef STAN_MATH_PRIM_ERR_CHECK_SUM_TO_ZERO_HPP
#define STAN_MATH_PRIM_ERR_CHECK_SUM_TO_ZERO_HPP

#include <stan/math/prim/fun/Eigen.hpp>
#include <stan/math/prim/meta.hpp>
#include <stan/math/prim/err/constraint_tolerance.hpp>
#include <stan/math/prim/err/make_iter_name.hpp>
#include <stan/math/prim/err/throw_domain_error.hpp>
#include <stan/math/prim/fun/to_ref.hpp>
#include <stan/math/prim/fun/value_of_rec.hpp>
#include <sstream>
#include <string>

namespace stan {
namespace math {

/**
* Throw an exception if the specified vector does not sum to 0.
* This function tests that the sum is within the tolerance specified by
* `CONSTRAINT_TOLERANCE`.
* This function only accepts Eigen vectors, statically
* typed vectors, not general matrices with 1 column.
* @tparam T A type inheriting from `Eigen::EigenBase`
* @param function Function name (for error messages)
* @param name Variable name (for error messages)
* @param theta Vector to test
* @throw `std::invalid_argument` if `theta` is a 0-vector
* @throw `std::domain_error` if the vector does not sum to zero
*/
template <typename T, require_matrix_t<T>* = nullptr>
void check_sum_to_zero(const char* function, const char* name, const T& theta) {
using std::fabs;
// the size-zero case is technically a valid sum-to-zero vector,
// but it cannot be unconstrained to anything
check_nonzero_size(function, name, theta);
auto&& theta_ref = to_ref(value_of_rec(theta));
if (unlikely(!(fabs(theta_ref.sum()) <= CONSTRAINT_TOLERANCE))) {
[&]() STAN_COLD_PATH {
std::stringstream msg;
scalar_type_t<T> sum = theta_ref.sum();
msg << "does not sum to zero.";
msg.precision(10);
msg << " sum(" << name << ") = " << sum << ", but should be ";
std::string msg_str(msg.str());
throw_domain_error(function, name, 0.0, msg_str.c_str());
}();
}
}

/**
* Throw an exception if any vector in a standard vector does not sum to 0.
* This function tests that the sum is within the tolerance specified by
* `CONSTRAINT_TOLERANCE`.
* @tparam T A standard vector with inner type inheriting from
* `Eigen::EigenBase`
* @param function Function name (for error messages)
* @param name Variable name (for error messages)
* @param theta Vector to test.
* @throw `std::invalid_argument` if `theta` is a 0-vector
* @throw `std::domain_error` if the vector does not sum to zero
*/
template <typename T, require_std_vector_t<T>* = nullptr>
void check_sum_to_zero(const char* function, const char* name, const T& theta) {
for (size_t i = 0; i < theta.size(); ++i) {
check_sum_to_zero(function, internal::make_iter_name(name, i).c_str(),
theta[i]);
}
}

} // namespace math
} // namespace stan
#endif
1 change: 1 addition & 0 deletions stan/math/rev/constraint.hpp
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#include <stan/math/rev/constraint/simplex_constrain.hpp>
#include <stan/math/rev/constraint/stochastic_column_constrain.hpp>
#include <stan/math/rev/constraint/stochastic_row_constrain.hpp>
#include <stan/math/rev/constraint/sum_to_zero_constrain.hpp>
#include <stan/math/rev/constraint/unit_vector_constrain.hpp>
#include <stan/math/rev/constraint/ub_constrain.hpp>

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