UofT Libraries is getting a new library services platform in January 2021.

Learn more about the change.

## Search Articles

2015, ISBN 1118326555, xii, 308 pages

The reference book for spatio-temporal modeling with INLA. The Bayesian approach is particularly effective at modeling large datasets including spatial and...

Bayesian statistical decision theory | Spatial analysis (Statistics) | advanced modeling | probability theory | spatial modeling | spatio-temporal models | Asymptotic distribution (Probability theory) | Analyse spatiale (Statistique) | R (Langage de programmation) | computing | spatial analysis | asymptotic distribution | Distribution asymptotique (Théorie des probabilités) | R (Computer program language) | Théorie de la décision bayésienne | R(computer language) | misaligned data | statistics | Probability & Statistics | Mathematics | Bayesian Analysis | Temporal databases | Mathematical models

Bayesian statistical decision theory | Spatial analysis (Statistics) | advanced modeling | probability theory | spatial modeling | spatio-temporal models | Asymptotic distribution (Probability theory) | Analyse spatiale (Statistique) | R (Langage de programmation) | computing | spatial analysis | asymptotic distribution | Distribution asymptotique (Théorie des probabilités) | R (Computer program language) | Théorie de la décision bayésienne | R(computer language) | misaligned data | statistics | Probability & Statistics | Mathematics | Bayesian Analysis | Temporal databases | Mathematical models

Book

The Annals of statistics, ISSN 0090-5364, 04/2010, Volume 38, Issue 2, pp. 808 - 835

We propose a two-sample test for the means of high-dimensional data when the data dimension is much larger than the sample size. Hotelling's classical T² test...

Statistical variance | High dimensional spaces | Sample size | Covariance | Genes | Eigenvalues | P values | Sample mean | Standard deviation | Covariance matrices | Gene-set testing | High dimension | Multiple comparison | Large p small n | Martingale central limit theorem | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Flexibility | Leukemia | 62H15 | large p small n | gene-set testing | multiple comparison | 62G10 | 60K35 | martingale central limit theorem

Statistical variance | High dimensional spaces | Sample size | Covariance | Genes | Eigenvalues | P values | Sample mean | Standard deviation | Covariance matrices | Gene-set testing | High dimension | Multiple comparison | Large p small n | Martingale central limit theorem | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Flexibility | Leukemia | 62H15 | large p small n | gene-set testing | multiple comparison | 62G10 | 60K35 | martingale central limit theorem

Journal Article

2017, Probability theory and stochastic modelling, ISBN 3662543222, Volume 80, xviii, 204 pages

Presenting tools to aid understanding of asymptotic theory and weakly dependent processes, this book is devoted to inequalities and limit theorems for...

Inequalities (Mathematics) | Markov processes | Central limit theorem | Asymptotic distribution (Probability theory) | Mathematics | Asymptotic expansions | Stochastic processes

Inequalities (Mathematics) | Markov processes | Central limit theorem | Asymptotic distribution (Probability theory) | Mathematics | Asymptotic expansions | Stochastic processes

Book

The Annals of statistics, ISSN 0090-5364, 6/2014, Volume 42, Issue 3, pp. 1166 - 1202

We propose a general method for constructing confidence intervals and statistical tests for single or low-dimensional components of a large parameter vector in...

Logistic regression | Generalized linear model | Linear regression | Eigenvalues | Inference | Non Gaussianity | Linear models | Estimators | Consistent estimators | Confidence interval | Central limit theorem | Sparsity | Lasso | Semiparametric efficiency | Multiple testing | Linear model | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Confidence intervals | Mathematical models | Normal distribution | Asymptotic methods | Generalized linear models | generalized linear model | lasso | 62J07 | multiple testing | semiparametric efficiency | linear model | sparsity | 62F25 | 62J12

Logistic regression | Generalized linear model | Linear regression | Eigenvalues | Inference | Non Gaussianity | Linear models | Estimators | Consistent estimators | Confidence interval | Central limit theorem | Sparsity | Lasso | Semiparametric efficiency | Multiple testing | Linear model | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Confidence intervals | Mathematical models | Normal distribution | Asymptotic methods | Generalized linear models | generalized linear model | lasso | 62J07 | multiple testing | semiparametric efficiency | linear model | sparsity | 62F25 | 62J12

Journal Article

2011, 2nd ed., For dummies, ISBN 0470911085, xiv, 370

This guide shows you how to collect, graph, and critique data; decipher distributions; calculate confidence intervals and hypothesis tests; analyze data with...

Statistics

Statistics

Book

Journal of applied probability, ISSN 0021-9002, 09/2013, Volume 50, Issue 3, pp. 760 - 771

The Hawkes process is a self-exciting point process with clustering effect whose intensity depends on its entire past history. It has wide applications in...

Hawkes process | Self-exciting process | Central limit theorem | Point process | Functional central limit theorem | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | 60G55 | point process | self-exciting process | 60F05 | functional central limit theorem

Hawkes process | Self-exciting process | Central limit theorem | Point process | Functional central limit theorem | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | 60G55 | point process | self-exciting process | 60F05 | functional central limit theorem

Journal Article

1971, Report /Instituut voor Toepassingen van de Wiskunde ;71-03, Volume 71-03., 13 leaves

Book

The Annals of statistics, ISSN 0090-5364, 10/2009, Volume 37, Issue 5B, pp. 2953 - 2989

Consider a random sample from a bivariate distribution function F in the max-domain of attraction of an extreme-value distribution function G. This G is...

Average linear density | Atoms | Sine function | Atomic spectra | Cauchy Lorentz distribution | Spectral index | Parametric models | Estimators | Logistics | Distribution functions | Moment constraint | Multivariate extremes | Functional central limit theorem | Tail dependence | National Health and Nutrition Examination Survey | Nonparametric maximum likelihood estimator | Local empirical process | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Estimating techniques | Simulation | Multivariate analysis | Maximum likelihood method | 62G05 | 60G70 | tail dependence | local empirical process | multivariate extremes | moment constraint | nonparametric maximum likelihood estimator | 62G30 | 62G32 | 60F17 | 60F05

Average linear density | Atoms | Sine function | Atomic spectra | Cauchy Lorentz distribution | Spectral index | Parametric models | Estimators | Logistics | Distribution functions | Moment constraint | Multivariate extremes | Functional central limit theorem | Tail dependence | National Health and Nutrition Examination Survey | Nonparametric maximum likelihood estimator | Local empirical process | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Estimating techniques | Simulation | Multivariate analysis | Maximum likelihood method | 62G05 | 60G70 | tail dependence | local empirical process | multivariate extremes | moment constraint | nonparametric maximum likelihood estimator | 62G30 | 62G32 | 60F17 | 60F05

Journal Article

2009, 2nd ed., History of mathematics, ISBN 9780821848999, Volume 35., xii, 195

Book

2000, EUI working paper. ECO, Volume no. 2000/1, 18

Book

2014, 2nd edition., Cambridge studies in advanced mathematics, ISBN 0521498848, Volume 142, xii, 472

"This classic work on empirical processes has been considerably expanded and revised from the original edition. When samples become large, the probability laws...

MATHEMATICS / Probability & Statistics / General | Central limit theorem

MATHEMATICS / Probability & Statistics / General | Central limit theorem

Book

The Annals of statistics, ISSN 0090-5364, 6/2009, Volume 37, Issue 3, pp. 1150 - 1171

We investigate invariant random fields on the sphere using a new type of spherical wavelets, called needlets. These are compactly supported in frequency and...

Cosmic microwave background radiation | Isotropy | Central limit theorem | Astrophysics | Approximation | Spherical harmonics | Milky Way Galaxy | Polynomials | Statistics | Angular separation | High-frequency asymptotics | Tests for Gaussianity and isotropy | Random fields | Spherical needlets | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Mathematical functions | Statistical analysis | Spheres | Asymptotic methods | Probability | random fields | tests for Gaussianity and isotropy | central limit theorem | spherical needlets | 62G20 | 62M40 | 60F17 | 60F05

Cosmic microwave background radiation | Isotropy | Central limit theorem | Astrophysics | Approximation | Spherical harmonics | Milky Way Galaxy | Polynomials | Statistics | Angular separation | High-frequency asymptotics | Tests for Gaussianity and isotropy | Random fields | Spherical needlets | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Mathematical functions | Statistical analysis | Spheres | Asymptotic methods | Probability | random fields | tests for Gaussianity and isotropy | central limit theorem | spherical needlets | 62G20 | 62M40 | 60F17 | 60F05

Journal Article

1987, 77

Book

Journal of applied probability, ISSN 0021-9002, 06/2011, Volume 48, Issue 2, pp. 527 - 546

Let X
n
be a sequence of integrable real random variables, adapted to a filtration (G
n
). Define C
n
= √{(1 / n)∑
k=1
n
X
k
− E(X
n+1 | G
n
)} and D
n
=...

Random probability measure | Urn model | Central limit theorem | Bayesian statistics | Predictive distribution | Poisson-Dirichlet process | Stable convergence | Empirical distribution | 60G57 | central limit theorem | empirical distribution | predictive distribution | urn model | random probability measure | 60B10 | stable convergence | 60F05 | 62F15

Random probability measure | Urn model | Central limit theorem | Bayesian statistics | Predictive distribution | Poisson-Dirichlet process | Stable convergence | Empirical distribution | 60G57 | central limit theorem | empirical distribution | predictive distribution | urn model | random probability measure | 60B10 | stable convergence | 60F05 | 62F15

Journal Article

Annals of the Institute of Statistical Mathematics, ISSN 1572-9052, 10/2016, Volume 70, Issue 1, pp. 99 - 129

As demonstrated in our previous work on
$${\varvec{T}}_{\!4}$$
T
4
, the space of phylogenetic trees with four leaves, the topological structure of the space...

Stratified manifold | Phylogenetic trees | Central limit theorem | Statistics for Business/Economics/Mathematical Finance/Insurance | Fréchet mean | Statistics, general | Statistics | Log map | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Phylogeny | Thyroid hormones | Trees | Leaves | Normal distribution | Strata | Phylogenetics | Gaussian distribution | Constraining

Stratified manifold | Phylogenetic trees | Central limit theorem | Statistics for Business/Economics/Mathematical Finance/Insurance | Fréchet mean | Statistics, general | Statistics | Log map | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Phylogeny | Thyroid hormones | Trees | Leaves | Normal distribution | Strata | Phylogenetics | Gaussian distribution | Constraining

Journal Article

Journal of theoretical probability, ISSN 0894-9840, 9/2018, Volume 31, Issue 3, pp. 1590 - 1605

We refine the classical Lindeberg–Feller central limit theorem by obtaining asymptotic bounds on the Kolmogorov distance, the Wasserstein distance, and the...

Stein’s method | Lindeberg–Feller central limit theorem | Kolmogorov metric | Wasserstein metric | Probability Theory and Stochastic Processes | Mathematics | Prokhorov metric | Statistics, general | Lindeberg index | 60F05 | Statistics & Probability | Physical Sciences | Science & Technology | Theorems | Random variables

Stein’s method | Lindeberg–Feller central limit theorem | Kolmogorov metric | Wasserstein metric | Probability Theory and Stochastic Processes | Mathematics | Prokhorov metric | Statistics, general | Lindeberg index | 60F05 | Statistics & Probability | Physical Sciences | Science & Technology | Theorems | Random variables

Journal Article

The Annals of statistics, ISSN 0090-5364, 12/2009, Volume 37, Issue 6B, pp. 4046 - 4087

In this paper, we introduce an asymptotic test procedure to assess the stability of volatilities and cross-volatilites of linear and nonlinear multivariate...

Economic models | Time series models | Mathematical theorems | Covariance | Time series | Critical values | Mathematical vectors | Random variables | Covariance matrices | Estimators | Change-points | Structural breaks | Multivariate time series | Functional central limit theorem | Multivariate GARCH models | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Probability | Algorithms | Volatility | 62M10 | structural breaks | multivariate GARCH models | multivariate time series | covariance | 60K35 | 91B84 | 60F17 | functional central limit theorem

Economic models | Time series models | Mathematical theorems | Covariance | Time series | Critical values | Mathematical vectors | Random variables | Covariance matrices | Estimators | Change-points | Structural breaks | Multivariate time series | Functional central limit theorem | Multivariate GARCH models | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Probability | Algorithms | Volatility | 62M10 | structural breaks | multivariate GARCH models | multivariate time series | covariance | 60K35 | 91B84 | 60F17 | functional central limit theorem

Journal Article

The Annals of statistics, ISSN 0090-5364, 10/2013, Volume 41, Issue 5, pp. 2391 - 2427

In this paper, we present a test for the maximal rank of the matrix-valued volatility process in the continuous Itô semimartingale framework. Our idea is based...

Brownian motion | Null hypothesis | Logical givens | Determinants | Matrices | High frequencies | Statistics | Estimators | Martingales | Perceptron convergence procedure | Stable convergence | Central limit theorem | High frequency data | Itô semimartingales | Homoscedasticity testing | Rank estimation | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Hypothesis testing | Matrix | Volatility | Ratings & rankings | high frequency data | rank estimation | 62E20 | 62M07 | homoscedasticity testing | stable convergence | 60F17 | 60F05

Brownian motion | Null hypothesis | Logical givens | Determinants | Matrices | High frequencies | Statistics | Estimators | Martingales | Perceptron convergence procedure | Stable convergence | Central limit theorem | High frequency data | Itô semimartingales | Homoscedasticity testing | Rank estimation | Statistics & Probability | Physical Sciences | Mathematics | Science & Technology | Studies | Hypothesis testing | Matrix | Volatility | Ratings & rankings | high frequency data | rank estimation | 62E20 | 62M07 | homoscedasticity testing | stable convergence | 60F17 | 60F05

Journal Article

Management science, ISSN 0025-1909, 5/2017, Volume 63, Issue 5, pp. 1625 - 1643

We propose and analyze robust optimization models of an inventory management problem, where cumulative purchase, inventory, and shortage costs over
n
periods...

central limit theorem | dynamic optimization | inventory management | robust optimization | Inventory management | Central limit theorem | Robust optimization | Dynamic optimization | Business & Economics | Operations Research & Management Science | Social Sciences | Management | Technology | Science & Technology | Inventory control | Methods

central limit theorem | dynamic optimization | inventory management | robust optimization | Inventory management | Central limit theorem | Robust optimization | Dynamic optimization | Business & Economics | Operations Research & Management Science | Social Sciences | Management | Technology | Science & Technology | Inventory control | Methods

Journal Article

1991, Dissertationes mathematicae = Rozprawy matematyczne, ISBN 8385116079, Volume 307., 64

Book

No results were found for your search.

Cannot display more than 1000 results, please narrow the terms of your search.