gwkokab.models.sundry ===================== .. py:module:: gwkokab.models.sundry .. autoapi-nested-parse:: This module contains generic implementation of models that do not fit into a narrow category on intrinsic or extrinsic parameter models. Functions --------- .. autoapisummary:: gwkokab.models.sundry.NDIsotropicAndTruncatedNormalMixture gwkokab.models.sundry.NDTwoTruncatedNormalMixture gwkokab.models.sundry.TwoTruncatedNormalMixture Package Contents ---------------- .. py:function:: NDIsotropicAndTruncatedNormalMixture(zeta: jaxtyping.ArrayLike, loc: jaxtyping.ArrayLike, scale: jaxtyping.ArrayLike, isotropic_low: jaxtyping.ArrayLike, isotropic_high: jaxtyping.ArrayLike, gaussian_low: Optional[jaxtyping.ArrayLike], gaussian_high: Optional[jaxtyping.ArrayLike], *, batch_dim: int = 1, validate_args: Optional[bool] = None) -> numpyro.distributions.MixtureGeneral General N-dimensional mixture model of an isotropic uniform distribution and a truncated normal distribution. .. math:: p(\mathbf{x}\mid\zeta,\boldsymbol{\mu},\boldsymbol{\sigma}) = (1-\zeta)\mathcal{U}(\mathbf{x}\mid \boldsymbol{a},\boldsymbol{b}) + \zeta\mathcal{N}_{[\boldsymbol{L}, \boldsymbol{U}]}(\mathbf{x}\mid \boldsymbol{\mu},\boldsymbol{\sigma}) where :math:`\mathcal{U}(\cdot)` is the isotropic uniform distribution between :math:`\boldsymbol{a}=\left< a_1, a_2, \ldots, a_N \right>` and :math:`\boldsymbol{b}=\left< b_1, b_2, \ldots, b_N \right>`, and :math:`\mathcal{N}_{[\boldsymbol{L}, \boldsymbol{U}]}(\cdot)` is the truncated normal distribution with mean :math:`\boldsymbol{\mu}=\left< \mu_1, \mu_2, \ldots, \mu_N \right>`, standard deviation :math:`\boldsymbol{\sigma}=\left< \sigma_1, \sigma_2, \ldots, \sigma_N \right>`, lower bound :math:`\boldsymbol{L}=\left< L_1, L_2, \ldots, L_N \right>`, and upper bound :math:`\boldsymbol{U}=\left< U_1, U_2, \ldots, U_N \right>`. :param zeta: The mixing probability of the second component. :type zeta: ArrayLike :param loc: The mean of the truncated normal distribution. :type loc: ArrayLike :param scale: The standard deviation of the truncated normal distribution. :type scale: ArrayLike :param isotropic_low: The lower bound of the isotropic uniform distribution. :type isotropic_low: ArrayLike :param isotropic_high: The upper bound of the isotropic uniform distribution. :type isotropic_high: ArrayLike :param gaussian_low: The lower bound of the truncated normal distribution. :type gaussian_low: Optional[ArrayLike] :param gaussian_high: The upper bound of the truncated normal distribution. :type gaussian_high: Optional[ArrayLike] :param batch_dim: The batch dimension of the distributions, by default 1 :type batch_dim: int, optional :param validate_args: Whether to validate the parameters of the distributions, by default None :type validate_args: Optional[bool], optional :returns: N-dimensional mixture model of an isotropic uniform distribution and a truncated normal distribution. :rtype: MixtureGeneral .. py:function:: NDTwoTruncatedNormalMixture(comp1_high: jaxtyping.ArrayLike, comp1_loc: jaxtyping.ArrayLike, comp1_low: jaxtyping.ArrayLike, comp1_scale: jaxtyping.ArrayLike, comp2_high: jaxtyping.ArrayLike, comp2_loc: jaxtyping.ArrayLike, comp2_low: jaxtyping.ArrayLike, comp2_scale: jaxtyping.ArrayLike, zeta: jaxtyping.ArrayLike, *, batch_dim: int = 1, validate_args: Optional[bool] = None) -> numpyro.distributions.MixtureGeneral General N-dimensional mixture model of two truncated normal distributions. :param comp1_high: The upper bound of the first truncated normal distribution. :type comp1_high: ArrayLike :param comp1_loc: The mean of the first truncated normal distribution. :type comp1_loc: ArrayLike :param comp1_low: The lower bound of the first truncated normal distribution. :type comp1_low: ArrayLike :param comp1_scale: The standard deviation of the first truncated normal distribution. :type comp1_scale: ArrayLike :param comp2_high: The upper bound of the second truncated normal distribution. :type comp2_high: ArrayLike :param comp2_loc: The mean of the second truncated normal distribution. :type comp2_loc: ArrayLike :param comp2_low: The lower bound of the second truncated normal distribution. :type comp2_low: ArrayLike :param comp2_scale: The standard deviation of the second truncated normal distribution. :type comp2_scale: ArrayLike :param zeta: The mixing proportion for the second component. :type zeta: ArrayLike :param batch_dim: The batch dimension for the distributions, by default 1 :type batch_dim: int, optional :param validate_args: Whether to validate the arguments, by default None :type validate_args: Optional[bool], optional :returns: N-dimensional mixture model of two truncated normal distributions. :rtype: MixtureGeneral .. py:function:: TwoTruncatedNormalMixture(comp1_high: Optional[jaxtyping.ArrayLike], comp1_loc: jaxtyping.ArrayLike, comp1_low: Optional[jaxtyping.ArrayLike], comp1_scale: jaxtyping.ArrayLike, comp2_high: Optional[jaxtyping.ArrayLike], comp2_loc: jaxtyping.ArrayLike, comp2_low: Optional[jaxtyping.ArrayLike], comp2_scale: jaxtyping.ArrayLike, zeta: jaxtyping.ArrayLike, *, validate_args: Optional[bool] = None) -> numpyro.distributions.MixtureGeneral Create a mixture model of two truncated normal distributions. :param comp1_high: Upper truncation for the first component. :type comp1_high: Optional[ArrayLike] :param comp1_loc: Location parameter for the first component. :type comp1_loc: ArrayLike :param comp1_low: Lower truncation for the first component. :type comp1_low: Optional[ArrayLike] :param comp1_scale: Scale parameter for the first component. :type comp1_scale: ArrayLike :param comp2_high: Upper truncation for the second component. :type comp2_high: Optional[ArrayLike] :param comp2_loc: Location parameter for the second component. :type comp2_loc: ArrayLike :param comp2_low: Lower truncation for the second component. :type comp2_low: Optional[ArrayLike] :param comp2_scale: Scale parameter for the second component. :type comp2_scale: ArrayLike :param zeta: Mixing proportion for the second component. :type zeta: ArrayLike :param validate_args: Whether to validate the arguments, by default None :type validate_args: Optional[bool], optional :returns: A mixture of two truncated normal distributions. :rtype: MixtureGeneral