def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self k = dist.k tau_e = dist.tau_e return r'${} \sim \text{{AR1}}(\mathit{{k}}={}, \mathit{{tau_e}}={})$'.format(name, get_variable_name(k), get_variable_name(tau_e))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu cov = dist.cov return r'${} \sim \text{MvGaussianRandomWalk}(\mathit{{mu}}={}, \mathit{{cov}}={})$'.format(name, get_variable_name(mu), get_variable_name(cov))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu sd = dist.sd return r'${} \sim \text{{GaussianRandomWalk}}(\mathit{{mu}}={}, \mathit{{sd}}={})$'.format(name, get_variable_name(mu), get_variable_name(sd))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self n = dist.n p = dist.p return r'${} \sim \text{{Multinomial}}(\mathit{{n}}={}, \mathit{{p}}={})$'.format(name, get_variable_name(n), get_variable_name(p))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self nu = dist.nu V = dist.V return r'${} \sim \text{{Wishart}}(\mathit{{nu}}={}, \mathit{{V}}={})$'.format(name, get_variable_name(nu), get_variable_name(V))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self theta = dist.theta psi = dist.psi return r'${} \sim \text{{ZeroInflatedPoisson}}(\mathit{{theta}}={}, \mathit{{psi}}={})$'.format(name, get_variable_name(theta), get_variable_name(psi))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self lower = dist.lower upper = dist.upper return r'${} \sim \text{{DiscreteUniform}}(\mathit{{lower}}={}, \mathit{{upper}}={})$'.format(name, get_variable_name(lower), get_variable_name(upper))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self name_eta = get_variable_name(dist.eta) name_cutpoints = get_variable_name(dist.cutpoints) return (r'${} \sim \text{{OrderedLogistic}}' r'(\mathit{{eta}}={}, \mathit{{cutpoints}}={}$' .format(name, name_eta, name_cutpoints))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu alpha = dist.alpha return r'${} \sim \text{{NegativeBinomial}}(\mathit{{mu}}={}, \mathit{{alpha}}={})$'.format(name, get_variable_name(mu), get_variable_name(alpha))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self q = dist.q beta = dist.beta return r'${} \sim \text{{DiscreteWeibull}}(\mathit{{q}}={}, \mathit{{beta}}={})$'.format(name, get_variable_name(q), get_variable_name(beta))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self n = dist.n p = dist.p psi = dist.psi return r'${} \sim \text{{ZeroInflatedBinomial}}(\mathit{{n}}={}, \mathit{{p}}={}, \mathit{{psi}}={})$'.format( name, get_variable_name(n), get_variable_name(p), get_variable_name(psi))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self nu = dist.nu mu = dist.mu cov = dist.cov return r'${} \sim \text{MvStudentTRandomWalk}(\mathit{{nu}}={}, \mathit{{mu}}={}, \mathit{{cov}}={})$'.format( name, get_variable_name(nu), get_variable_name(mu), get_variable_name(cov))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self lower = dist.lower upper = dist.upper name = r'\text{%s}' % name return r'${} \sim \text{{DiscreteUniform}}(\mathit{{lower}}={},~\mathit{{upper}}={})$'.format(name, get_variable_name(lower), get_variable_name(upper))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu w = dist.w sd = dist.sd return r'${} \sim \text{{NormalMixture}}(\mathit{{w}}={}, \mathit{{mu}}={}, \mathit{{sigma}}={})$'.format( name, get_variable_name(w), get_variable_name(mu), get_variable_name(sd))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self omega = dist.omega alpha_1 = dist.alpha_1 beta_1 = dist.beta_1 return r'${} \sim \text{GARCH}(1, 1, \mathit{{omega}}={}, \mathit{{alpha_1}}={}, \mathit{{beta_1}}={})$'.format( name, get_variable_name(omega), get_variable_name(alpha_1), get_variable_name(beta_1))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self alpha = dist.alpha beta = dist.beta name = r'\text{%s}' % name return r'${} \sim \text{{BetaBinomial}}(\mathit{{alpha}}={},~\mathit{{beta}}={})$'.format(name, get_variable_name(alpha), get_variable_name(beta))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu alpha = dist.alpha psi = dist.psi return r'${} \sim \text{{ZeroInflatedNegativeBinomial}}(\mathit{{mu}}={}, \mathit{{alpha}}={}, \mathit{{psi}}={})$'.format( name, get_variable_name(mu), get_variable_name(alpha), get_variable_name(psi))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self n = dist.n p = dist.p name = r'\text{%s}' % name return r'${} \sim \text{{Binomial}}(\mathit{{n}}={},~\mathit{{p}}={})$'.format(name, get_variable_name(n), get_variable_name(p))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self alpha = dist.alpha beta = dist.beta name = r'\text{%s}' % name return r'${} \sim \text{{NegativeBinomial}}(\mathit{{alpha}}={},~\mathit{{beta}}={})$'.format(name, get_variable_name(alpha), get_variable_name(beta))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self theta = dist.theta psi = dist.psi name = r'\text{%s}' % name return r'${} \sim \text{{ZeroInflatedPoisson}}(\mathit{{theta}}={},~\mathit{{psi}}={})$'.format(name, get_variable_name(theta), get_variable_name(psi))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu alpha = dist.alpha name = r'\text{%s}' % name return r'${} \sim \text{{NegativeBinomial}}(\mathit{{mu}}={},~\mathit{{alpha}}={})$'.format(name, get_variable_name(mu), get_variable_name(alpha))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu sigma = dist.sigma name = r'\text{%s}' % name return r'${} \sim \text{{GaussianRandomWalk}}(\mathit{{mu}}={},~\mathit{{sigma}}={})$'.format(name, get_variable_name(mu), get_variable_name(sigma))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self q = dist.q beta = dist.beta name = r'\text{%s}' % name return r'${} \sim \text{{DiscreteWeibull}}(\mathit{{q}}={},~\mathit{{beta}}={})$'.format(name, get_variable_name(q), get_variable_name(beta))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.innov.mu cov = dist.innov.cov name = r'\text{%s}' % name return r'${} \sim \text{MvGaussianRandomWalk}(\mathit{{mu}}={},~\mathit{{cov}}={})$'.format(name, get_variable_name(mu), get_variable_name(cov))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu nu = dist.nu Sigma = dist.Sigma return r'${} \sim \text{{MvStudentT}}(\mathit{{nu}}={}, \mathit{{mu}}={}, \mathit{{Sigma}}={})$'.format( name, get_variable_name(nu), get_variable_name(mu), get_variable_name(Sigma))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self n = dist.n p = dist.p psi = dist.psi return r'${} \sim \text{{ZeroInflatedBinomial}}(\mathit{{n}}={}, \mathit{{p}}={}, \mathit{{psi}}={})$'.format(name, get_variable_name(n), get_variable_name(p), get_variable_name(psi))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self nu = dist.innov.nu mu = dist.innov.mu cov = dist.innov.cov name = r"\text{%s}" % name return r"${} \sim \text{MvStudentTRandomWalk}(\mathit{{nu}}={},~\mathit{{mu}}={},~\mathit{{cov}}={})$".format( name, get_variable_name(nu), get_variable_name(mu), get_variable_name(cov))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu w = dist.w sd = dist.sd return r'${} \sim \text{{NormalMixture}}(\mathit{{w}}={}, \mathit{{mu}}={}, \mathit{{sigma}}={})$'.format(name, get_variable_name(w), get_variable_name(mu), get_variable_name(sd))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self omega = dist.omega alpha_1 = dist.alpha_1 beta_1 = dist.beta_1 return r'${} \sim \text{GARCH}(1, 1, \mathit{{omega}}={}, \mathit{{alpha_1}}={}, \mathit{{beta_1}}={})$'.format(name, get_variable_name(omega), get_variable_name(alpha_1), get_variable_name(beta_1))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu try: cov = dist.cov except AttributeErrir: cov = dist.chol_cov return r'${} \sim \text{{MvNormal}}(\mathit{{mu}}={}, \mathit{{cov}}={})$'.format( name, get_variable_name(mu), get_variable_name(cov))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self N = dist.N n = dist.n k = dist.k name = r'\text{%s}' % name return r'${} \sim \text{{HyperGeometric}}(\mathit{{N}}={},~\mathit{{n}}={}, ,~\mathit{{k}}={})$'.format( name, get_variable_name(N), get_variable_name(n), get_variable_name(k))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self rt = dist.rt location = dist.location scale = dist.scale name = r'\text{%s}' % name return r'${} \sim \text{{King}}(\mathit{{loc}}={},\mathit{{scale}}={},\mathit{{tidal_radius}}={})$'.format( name, get_variable_name(location), get_variable_name(scale), get_variable_name(rt))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu nu = dist.nu name_nu = get_variable_name(nu) name_mu = get_variable_name(mu) return (r'${} \sim \text{{MvStudentT}}' r'(\mathit{{nu}}={}, \mathit{{mu}}={}, ' r'{})$'.format(name, name_nu, name_mu, self._repr_cov_params(dist)))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self nu = dist.innov.nu mu = dist.innov.mu cov = dist.innov.cov name = r'\text{%s}' % name return r'${} \sim \text{MvStudentTRandomWalk}(\mathit{{nu}}={},~\mathit{{mu}}={},~\mathit{{cov}}={})$'.format(name, get_variable_name(nu), get_variable_name(mu), get_variable_name(cov))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu nu = dist.nu name_nu = get_variable_name(nu) name_mu = get_variable_name(mu) return (r'${} \sim \text{{MvStudentT}}' r'(\mathit{{nu}}={}, \mathit{{mu}}={}, ' r'{})$' .format(name, name_nu, name_mu, self._repr_cov_params(dist)))
def _repr_cov_params(self, dist=None): if dist is None: dist = self if self._cov_type == 'chol': chol = get_variable_name(self.chol) return r'\mathit{{chol}}={}'.format(chol) elif self._cov_type == 'cov': cov = get_variable_name(self.cov) return r'\mathit{{cov}}={}'.format(cov) elif self._cov_type == 'tau': tau = get_variable_name(self.tau) return r'\mathit{{tau}}={}'.format(tau)
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu nu = dist.nu Sigma = dist.Sigma name_nu = get_variable_name(nu) name_mu = get_variable_name(mu) name_sigma = get_variable_name(Sigma) return (r'${} \sim \text{{MvStudentT}}' r'(\mathit{{nu}}={}, \mathit{{mu}}={}, ' r'\mathit{{Sigma}}={})$'.format(name, name_nu, name_mu, name_sigma))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self n = dist.n p = dist.p psi = dist.psi name_n = get_variable_name(n) name_p = get_variable_name(p) name_psi = get_variable_name(psi) return (r'${} \sim \text{{ZeroInflatedBinomial}}' r'(\mathit{{n}}={}, \mathit{{p}}={}, ' r'\mathit{{psi}}={})$'.format(name, name_n, name_p, name_psi))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self omega = dist.omega alpha_1 = dist.alpha_1 beta_1 = dist.beta_1 name = r"\text{%s}" % name return r"${} \sim \text{GARCH}(1,~1,~\mathit{{omega}}={},~\mathit{{alpha_1}}={},~\mathit{{beta_1}}={})$".format( name, get_variable_name(omega), get_variable_name(alpha_1), get_variable_name(beta_1), )
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self n = dist.n p = dist.p psi = dist.psi name_n = get_variable_name(n) name_p = get_variable_name(p) name_psi = get_variable_name(psi) return (r'${} \sim \text{{ZeroInflatedBinomial}}' r'(\mathit{{n}}={}, \mathit{{p}}={}, ' r'\mathit{{psi}}={})$' .format(name, name_n, name_p, name_psi))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu alpha = dist.alpha psi = dist.psi name_mu = get_variable_name(mu) name_alpha = get_variable_name(alpha) name_psi = get_variable_name(psi) return (r'${} \sim \text{{ZeroInflatedNegativeBinomial}}' r'(\mathit{{mu}}={}, \mathit{{alpha}}={}, ' r'\mathit{{psi}}={})$' .format(name, name_mu, name_alpha, name_psi))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu alpha = dist.alpha psi = dist.psi name_mu = get_variable_name(mu) name_alpha = get_variable_name(alpha) name_psi = get_variable_name(psi) return (r'${} \sim \text{{ZeroInflatedNegativeBinomial}}' r'(\mathit{{mu}}={}, \mathit{{alpha}}={}, ' r'\mathit{{psi}}={})$'.format(name, name_mu, name_alpha, name_psi))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self p = dist.p name = r'\text{%s}' % name return r'${} \sim \text{{Categorical}}(\mathit{{p}}={})$'.format( name, get_variable_name(p))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu name = r'\text{%s}' % name return r'${} \sim \text{{Poisson}}(\mathit{{mu}}={})$'.format( name, get_variable_name(mu))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self gamma = dist.gamma name = r'\text{%s}' % name return r'${} \sim \text{{EFF}}(\mathit{{\gamma}}={})$'.format( name, get_variable_name(gamma))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self scale = dist.scale name = r'\text{%s}' % name return r'${} \sim \text{{EDSD}}(\mathit{{scale}}={})$'.format( name, get_variable_name(scale))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self dt = dist.dt name = r'\text{%s}' % name return r'${} \sim \text{EulerMaruyama}(\mathit{{dt}}={})$'.format(name, get_variable_name(dt))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self p = dist.p name = r'\text{%s}' % name return r'${} \sim \text{{Categorical}}(\mathit{{p}}={})$'.format(name, get_variable_name(p))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self mu = dist.mu name = r'\text{%s}' % name return r'${} \sim \text{{Poisson}}(\mathit{{mu}}={})$'.format(name, get_variable_name(mu))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self p = dist.p return r'${} \sim \text{{Geometric}}(\mathit{{p}}={})$'.format( name, get_variable_name(p))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self a = dist.a return r'${} \sim \text{{Dirichlet}}(\mathit{{a}}={})$'.format(name, get_variable_name(a))
def _repr_latex_(self, name=None, dist=None): if dist is None: dist = self p = dist.p return r'${} \sim \text{{Geometric}}(\mathit{{p}}={})$'.format(name, get_variable_name(p))