Stochastic Limit Theory has become a standard reference in its field. This new edition offers updated and improved results and an extended range of topics. It works both as a textbook and as an account of recent work in a field of particular interest to econometricians.
Stochastic Limit Theory has become a standard reference in its field. This new edition offers updated and improved results and an extended range of topics. It works both as a textbook and as an account of recent work in a field of particular interest to econometricians.
James Davidson is Emeritus Professor of Econometrics at the University of Exeter.
Inhaltsangabe
I Mathematics 1: Sets and Numbers 2: Limits, Sequences, and Sums 3: Measure 4: Integration 5: Metric Spaces 6: Topology II Probability 7: Probability Spaces 8: Random Variables 9: Expectations 10: Conditioning 11: Characteristic Functions III Theory of Stochastic Processes 12: Stochastic Processes 13: Time Series Models 14: Dependence 15: Mixing 16: Martingales 17: Mixingales 18: Near-Epoch Dependence IV The Law of Large Numbers 19: Stochastic Convergence 20: Convergence in Lp Norm 21: The Strong Law of Large Numbers 22: Uniform Stochastic Convergence V The Central Limit Theorem 23: Weak Convergence of Distributions 24: The Classical Central Limit Theorem 25: CLTs for Dependent Processes 26: Extensions and Complement VI The Functional Central Limit Theorem 27: Measures on Metric Spaces 28: Stochastic Processes in Continuous Time 29: Weak Convergence 30: Càdlàg Functions 31: FCLTs for Dependent Variables 32: Weak Convergence to Stochastic Integrals
I Mathematics 1: Sets and Numbers 2: Limits, Sequences, and Sums 3: Measure 4: Integration 5: Metric Spaces 6: Topology II Probability 7: Probability Spaces 8: Random Variables 9: Expectations 10: Conditioning 11: Characteristic Functions III Theory of Stochastic Processes 12: Stochastic Processes 13: Time Series Models 14: Dependence 15: Mixing 16: Martingales 17: Mixingales 18: Near-Epoch Dependence IV The Law of Large Numbers 19: Stochastic Convergence 20: Convergence in Lp Norm 21: The Strong Law of Large Numbers 22: Uniform Stochastic Convergence V The Central Limit Theorem 23: Weak Convergence of Distributions 24: The Classical Central Limit Theorem 25: CLTs for Dependent Processes 26: Extensions and Complement VI The Functional Central Limit Theorem 27: Measures on Metric Spaces 28: Stochastic Processes in Continuous Time 29: Weak Convergence 30: Càdlàg Functions 31: FCLTs for Dependent Variables 32: Weak Convergence to Stochastic Integrals
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