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(21 - 40 of 75)
Pages
- Title
- Higher Connectivity of Fiber Graphs of Gröbner Bases, AS2012 Special Volume, part 2: This issue includes a second series of papers from talks, posters and collaborations resulting from and inspired by the Algebraic Statistics in the Alleghenies Conference at Penn State, which took place in July 2012.
- Creator
- Potka, Samu
- Date
- 2013, 2013
- Description
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Fiber graphs of Gröbner bases from contingency tables are important in statistical hypothesis testing, where one studies random walks on these...
Show moreFiber graphs of Gröbner bases from contingency tables are important in statistical hypothesis testing, where one studies random walks on these graphs using the Metropolis-Hastings algorithm. The connectivity of the graphs has implications on how fast the algorithm converges. In this paper, we study a class of ber graphs with elementary combinatorial techniques and provide results that support a recent conjecture of Engström: the connectivity is given by the minimum vertex degree.
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- Journal of Algebraic Statistics
- Title
- An Iterative Method Converging to a Positive Solution of Certain Systems of Polynomial Equations
- Creator
- Cartwright, Dustin
- Date
- 2011, 2011
- Description
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We present a numerical algorithm for finding real non-negative solutions to a certain class of polynomial equations. Our methods are based on...
Show moreWe present a numerical algorithm for finding real non-negative solutions to a certain class of polynomial equations. Our methods are based on the expectation maximization and iterative proportional fitting algorithms, which are used in statistics to find maximum likelihood parameters for certain classes of statistical models. Since our algorithm works by iteratively improving an approximate solution, we find approximate solutions in the cases when there are no exact solutions, such as overconstrained systems.
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- Journal of Algebraic Statistics
- Title
- Geometry of Higher-Order Markov Chains, AS2012 Special Volume, part 1: This issue includes a second series of papers from talks, posters and collaborations resulting from and inspired by the Algebraic Statistics in the Alleghenies Conference at Penn State, which took place in July 2012.
- Creator
- Sturmfels, Bernd
- Date
- 2012, 2012
- Description
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We determine an explicit Gr ?obner basis, consisting of linear forms and determinantal quadrics, for the prime ideal of Raftery’s mixture...
Show moreWe determine an explicit Gr ?obner basis, consisting of linear forms and determinantal quadrics, for the prime ideal of Raftery’s mixture transition distribution model for Markov chains. When the states are binary, the corresponding projective variety is a linear space, the model itself consists of two simplices in a cross-polytope, and the likelihood function typically has two local maxima. In the general non-binary case, the model corresponds to a cone over a Segre variety.
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- Journal of Algebraic Statistics
- Title
- Betti Numbers of Cut Ideals of Trees, AS2012 Special Volume, part 2: This issue includes a second series of papers from talks, posters and collaborations resulting from and inspired by the Algebraic Statistics in the Alleghenies Conference at Penn State, which took place in July 2012.
- Creator
- Potka, Samu, Sarmiento, Camilo
- Date
- 2013, 2013
- Description
-
Cut ideals, introduced by Sturmfels and Sullivant, are used in phylogenetics and algebraic statistics. We study the minimal free resolutions...
Show moreCut ideals, introduced by Sturmfels and Sullivant, are used in phylogenetics and algebraic statistics. We study the minimal free resolutions of cut ideals of tree graphs. By employing basic methods from topological combinatorics, we obtain upper bounds for the Betti numbers of this type of ideals. These take the form of simple formulas on the number of vertices, which arise from the enumeration of induced subgraphs of certain incomparability graphs associated to the edge sets of trees.
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- Journal of Algebraic Statistics
- Title
- The geometry of Sloppiness
- Creator
- Dufresne, Emilie, Harrington , Heather A, Raman, Dhruva V
- Date
- 2018, 2018-09-24
- Description
-
The use of mathematical models in the sciences often requires the estimation of unknown parameter values from data. Sloppiness provides...
Show moreThe use of mathematical models in the sciences often requires the estimation of unknown parameter values from data. Sloppiness provides information about the uncertainty of this task. In this paper, we develop a precise mathematical foundation for sloppiness and define rigorously its key concepts, such as `model manifold', in relation to concepts of structural identifiability. We redefine sloppiness conceptually as a comparison between the premetric on parameter space induced by measurement noise and a reference metric. This opens up the possibility of alternative quantification of sloppiness, beyond the standard use of the Fisher Information Matrix, which assumes that parameter space is equipped with the usual Euclidean and the measurement error is infinitesimal. Applications include parametric statistical models, explicit time dependent models, and ordinary differential equation models.
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- Journal of Algebraic Statistics
- Title
- Mixture models for rating data: the method of moments via Groebner bases
- Creator
- Iannario, Maria, Simone, Rosaria
- Date
- 2017, 2017-12-26
- Description
-
A recent thread of research in ordinal data analysis involves a class of mixture models that designs the responses as the combination of the...
Show moreA recent thread of research in ordinal data analysis involves a class of mixture models that designs the responses as the combination of the two main aspects driving the decision pro- cess: a feeling and an uncertainty components. This novel paradigm has been proven flexible to account also for overdispersion. In this context, Groebner bases are exploited to estimate model parameters by implementing the method of moments. In order to strengthen the validity of the moment procedure so derived, alternatives parameter estimates are tested by means of a simulation experiment. Results show that the moment estimators are satisfactory per se, and that they significantly reduce the bias and perform more efficiently than others when they are set as starting values for the Expectation-Maximization algorithm.
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- Journal of Algebraic Statistics
- Title
- Ideal-Theoretic Strategies for Asymptotic Approximation of Marginal Likelihood Integrals
- Creator
- Lin, Shaowei
- Date
- 2017, 2017-02-08
- Description
-
The accurate asymptotic evaluation of marginal likelihood integrals is a fundamental problem in Bayesian statistics. Following the approach...
Show moreThe accurate asymptotic evaluation of marginal likelihood integrals is a fundamental problem in Bayesian statistics. Following the approach introduced by Watanabe, we translate this into a problem of computational algebraic geometry, namely, to determine the real log canonical threshold of a polynomial ideal, and we present effective methods for solving this problem. Our results are based on resolution of singularities. They apply to parametric models where the Kullback-Leibler distance is upper and lower bounded by scalar multiples of some sum of squared real analytic functions. Such models include finite state discrete models.
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- Journal of Algebraic Statistics
- Title
- Unimodular hierarchical models and their Graver bases
- Creator
- Bernstein, Daniel Irving, O'Neill, Christopher
- Date
- 2017, 2017-12-26
- Description
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Given a simplicial complex whose vertices are labeled with positive integers, one can associate a vector configuration whose corresponding...
Show moreGiven a simplicial complex whose vertices are labeled with positive integers, one can associate a vector configuration whose corresponding toric variety is the Zariski closure of a hierarchical model. We classify all the vertex-weighted simplicial complexes that give rise to unimodular vector configurations. We also provide a combinatorial characterization of their Graver bases.
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- Journal of Algebraic Statistics
- Title
- Mixtures and products in two graphical models
- Creator
- Seigal,Anna, Montufar, Guido
- Date
- 2018, 2018-09-24
- Description
-
We compare two statistical models of three binary random variables. One is a mixture model and the other is a product of mixtures model called...
Show moreWe compare two statistical models of three binary random variables. One is a mixture model and the other is a product of mixtures model called a restricted Boltzmann machine. Although the two models we study look different from their parametrizations, we show that they represent the same set of distributions on the interior of the probability simplex, and are equal up to closure. We give a semi-algebraic description of the model in terms of six binomial inequalities and obtain closed form expressions for the maximum likelihood estimates. We briefly discuss extensions to larger models.
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- Journal of Algebraic Statistics
- Title
- Markov bases for two-way change-point models of ladder determinantal tables
- Creator
- Aoki, Satoshi, Hibi, Takayuki
- Date
- 2017, 2017-02-08
- Description
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To evaluate the goodness-of-fit of a statistical model to given data, calculating a conditional p value by a Markov chain Monte Carlo method...
Show moreTo evaluate the goodness-of-fit of a statistical model to given data, calculating a conditional p value by a Markov chain Monte Carlo method is one of the effective approaches. For this purpose, a Markov basis plays an important role because it guarantees the connectivity of the chain, which is needed for unbiasedness of the estimation, and therefore is investigated in various settings such as incomplete tables or subtable sum constraints. In this paper, we consider the two-way change-point model for the ladder determinantal table, which is an extension of these two previous works, i.e., works on incomplete tables by Aoki and Takemura (2005, J. Stat. Comput. Simulat.) and subtable some constraints by Hara, Takemura and Yoshida (2010, J. Pure Appl. Algebra). Our main result is based on the theory of Gr ?obner basis for the distributive lattice. We give a numerical example for actual data.
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- Journal of Algebraic Statistics
- Title
- Cubature Rules and Expected Value of Some Complex Functions, Special Volume in honor of memory of S.E.Fienberg
- Creator
- Fassino, Claudia, Riccomagno, Eva, Rogantin, Maria Piera
- Date
- 2019, 2019-04-12
- Description
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The expected value of some complex valued random vectors is computed by means of the indicator function of a designed experiment as known in...
Show moreThe expected value of some complex valued random vectors is computed by means of the indicator function of a designed experiment as known in algebraic statistics. The general theory is set-up and results are obtained for finite discrete random vectors and the Gaussian random vector. The precision space of some cubature rules/designed experiments is determined.
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- Journal of Algebraic Statistics
- Title
- Strongly Robust Toric Ideals in Codimension 2, Special Volume in honor of memory of S.E.Fienberg
- Creator
- Sullivant ,Seth
- Date
- 2019, 2019-04-12
- Description
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A homogeneous ideal is robust if its universal Gr ?obner basis is also a minimal generating set. For toric ideals, one has the stronger...
Show moreA homogeneous ideal is robust if its universal Gr ?obner basis is also a minimal generating set. For toric ideals, one has the stronger definition: A toric ideal is strongly robust if its Graver basis equals the set of indispensable binomials. We characterize the codimension 2 strongly robust toric ideals by their Gale diagrams. This gives a positive answer to a question of Petrovi?, Thoma, and Vladoiu in the case of codimension 2 toric ideals.
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- Journal of Algebraic Statistics
- Title
- Maximum Likelihood for Matrices with Rank Constraints
- Creator
- Hauenstein, Jonathan, Rodriguez, Jose Israel, Sturmfels, Bernd
- Date
- 2014, 2014-04-30
- Description
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Maximum likelihood estimation is a fundamental optimization problem in statistics. We study this problem on manifolds of matrices with bounded...
Show moreMaximum likelihood estimation is a fundamental optimization problem in statistics. We study this problem on manifolds of matrices with bounded rank. These represent mixtures of distributions of two independent discrete random variables. We determine the maximum likelihood degree for a range of determinantal varieties, and we apply numerical algebraic geometry to compute all critical points of their likelihood functions. This led to the discovery of maximum likelihood duality between matrices of complementary ranks, a result proved subsequently by Draisma and Rodriguez.
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- Journal of Algebraic Statistics
- Title
- Generic Identification of Binary-Valued Hidden Markov Processes
- Creator
- Schönhuth, Alexander
- Date
- 2014, 2014-04-30
- Description
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The generic identification problem is to decide whether a stochastic process (X_t) is a hidden Markov process and if yes to infer its...
Show moreThe generic identification problem is to decide whether a stochastic process (X_t) is a hidden Markov process and if yes to infer its parameters for all but a subset of parametrizations that form a lower-dimensional subvariety in parameter space. Partial answers so far available depend on extra assumptions on the processes, which are usually centered around stationarity. Here we present a general solution for binary-valued hidden Markov processes. Our approach is rooted in algebraic statistics hence it is geometric in nature. We find that the algebraic varieties associated with the probability distributions of binary-valued hidden Markov processes are zero sets of determinantal equations which draws a connection to well-studied objects from algebra. As a consequence, our solution allows for algorithmic implementation based on elementary (linear) algebraic routines.
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- Journal of Algebraic Statistics
- Title
- Estimation for Dyadic-Dependent Exponential Random Graph Models
- Creator
- Yang, Xiaolin, Rinaldo, Alessandro, Fienberg, Stephen E.
- Date
- 2014, 2014-04-30
- Description
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Graphs are the primary mathematical representation for networks, with nodes or vertices corresponding to units (e.g., individuals) and edges...
Show moreGraphs are the primary mathematical representation for networks, with nodes or vertices corresponding to units (e.g., individuals) and edges corresponding to relationships. Exponential Random Graph Models (ERGMs) are widely used for describing network data because of their simple structure as an exponential function of a sum of parameters multiplied by their corresponding sufficient statistics. As with other exponential family settings the key computational difficulty is determining the normalizing constant for the likelihood function, a quantity that depends only on the data. In ERGMs for network data, the normalizing constant in the model often makes the parameter estimation intractable for large graphs, when the model involves dependence among dyads in the graph. One way to deal with this problem is to approximate the likelihood function by something tractable, e.g., by using the method of pseudo-likelihood estimation suggested in the early literature. In this paper, we describe the family of ERGMs and explain the increasing complexity that arises from imposing different edge dependence and homogeneous parameter assumptions. We then compare maximum likelihood (ML) and maximum pseudo-likelihood (MPL) estimation schemes with respect to existence and related degeneracy properties for ERGMs involving dependencies among dyads.
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- Journal of Algebraic Statistics
- Title
- A Family of Quasisymmetry Models
- Creator
- Kateri, Maria, Mohammadi, Fatemeh, Sturmfels, Bernd
- Date
- 2015, 2015-06-11
- Description
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We present a one-parameter family of models for square contingency tables that interpolates between the classical quasisymmetry model and its...
Show moreWe present a one-parameter family of models for square contingency tables that interpolates between the classical quasisymmetry model and its Pearsonian analogue. Algebraically, this corresponds to deformations of toric ideals associated with graphs. Our discussion of the statistical issues centers around maximum likelihood estimation.
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- Journal of Algebraic Statistics
- Title
- On the Connectivity of Fiber Graphs
- Creator
- Hemmecke, Raymond, Windisch, Tobias
- Date
- 2015, 2015-06-11
- Description
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We consider the connectivity of fiber graphs with respect to Gröbner basis and Graver basis moves. First, we present a sequence of fiber...
Show moreWe consider the connectivity of fiber graphs with respect to Gröbner basis and Graver basis moves. First, we present a sequence of fiber graphs using moves from a Gröbner basis and prove that their edge-connectivity is lowest possible and can have an arbitrarily large distance from the minimal degree. We then show that graph-theoretic properties of fiber graphs do not depend on the size of the right-hand side. This provides a counterexample to a conjecture of Engström on the node-connectivity of fiber graphs. Our main result shows that the edge-connectivity in all fiber graphs of this counterexample is best possible if we use moves from Graver basis instead.
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- Journal of Algebraic Statistics
- Title
- The precision space of interpolatory cubature formulæ
- Creator
- Fassino, Claudia, Riccomagno, Eva
- Date
- 2015, 2015-06-11
- Description
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Methods from Commutative Algebra and Numerical Analysis are combined to address a problem common to many disciplines: the estimation of the...
Show moreMethods from Commutative Algebra and Numerical Analysis are combined to address a problem common to many disciplines: the estimation of the expected value of a polynomial of a random vector using a linear combination of a finite number of its values. In this work we remark on the error estimation in cubature formulæ for polynomial functions and introduce the notion of a precision space for a cubature rule.
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- Journal of Algebraic Statistics
- Title
- The degeneration of the Grassmannian into a toric variety and the calculation of the eigenspaces of a torus action
- Creator
- Witaszek, Jakub
- Date
- 2015, 2015-06-11
- Description
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Using the method of degenerating a Grassmannian into a toric variety, we calculate formulas for the dimensions of the eigenspaces of the...
Show moreUsing the method of degenerating a Grassmannian into a toric variety, we calculate formulas for the dimensions of the eigenspaces of the action of an n-dimensional torus on a Grassmannian of planes in an n-dimensional space.
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- Journal of Algebraic Statistics
- Title
- Varieties with maximum likelihood degree one
- Creator
- Huh, June
- Date
- 2014, 2014-04-30
- Description
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We show that algebraic varieties with maximum likelihood degree one are exactly the images of reduced A-discriminantal varieties under...
Show moreWe show that algebraic varieties with maximum likelihood degree one are exactly the images of reduced A-discriminantal varieties under monomial maps with finite fibers. The maximum likelihood estimator corresponding to such a variety is Kapranov’s Horn uniformization. This extends Kapranov’s characterization of A-discriminantal hypersurfaces to varieties of arbitrary codimension.
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- Journal of Algebraic Statistics