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Introduction; Simulation Study of Performance of MBB in Overall Mean Estimation Problem for APC Time Series; 1 Introduction; 2 Theoretical Background; 3 Simulation Study; 4 Conclusions; References; Parametric Estimation Problem for a Time Periodic Signal in a Periodic Noise; 1 Introduction; 2 Drift Estimation from a Continuous Time Observation; 2.1 Likelihood; 2.2 Consistency of the Estimator; 2.3 Consistency and Efficiency When f(t,θ)=θf(t) ; 3 Drift Estimation from a Discrete Time Observation; 3.1 Consistency of the Estimator ; 3.2 Study of the Case f(t,θ)=θf(t) ; 4 Simulation
5 ConclusionReferences; Damage Assessment of Rolling Element Bearing Using Cyclostationary Processing of AE Signals with Electromagnetic Interference; 1 Introduction; 2 Problem Description; 3 Experimental Set-up; 4 Results; 5 Conclusion; References; The Stochastic Recurrence Structure of Geophysical Phenomena; 1 Introduction; 2 Annual Variation of Geophysical Processes; 3 Daily Variation; 4 The Properties of Annual and Daily Characteristic Estimators; 5 Conclusions; References; Influence of Different Signal Characteristics on PAR Model Stability; 1 Introduction
2 Periodic Autoregressive (PAR) Model2.1 Non-Gaussian Noise; 3 Motivation; 4 Influence of Non-Gaussian Noise to PAR Estimation; 4.1 Methodology; 4.2 Simulation Results; 5 Influence to PAR Estimation for Different Number of Period Repetitions; 5.1 Methodology; 5.2 Simulations; 6 Conclusions; References; Limiting Distributions for Explosive PAR(1) Time Series with Strongly Mixing Innovation; 1 Introduction; 2 Background : PAR(1) Time Series; 3 Explosive Asymptotic Behaviour of the Model; 4 Least Squares Estimation of the Coefficients; 5 Estimation of φ; 6 Simulation; References
PARMA Models with Applications in R1 Introduction; 2 PARMA Time Series Analysis; 2.1 Identification of PC-T Structure; 2.2 Estimation of PARMA Parameters; 2.3 Goodness of Fit and Model Selection; 3 Real Data Example; 3.1 Data; 3.2 Non-parametric Spectral Analysis; 3.3 Preliminary Identification and Conditioning; 3.4 Identification; 3.5 Model Fitting; 3.6 Short Time Prediction for PAR Models; 4 Simulated Data Example; 5 Conclusions; References; Multidimensional Analysis of New Zealand Electricity Prices; 1 Introduction; 2 Main Features of New Zealand Electricity Prices
2.1 New Zealand Electricity Market2.2 Relationship Between Respective Price Data Corresponding to Analysed Nodes; 2.3 Relationship Between Price Data and Deterministic Factors; 3 Multivariate Autoregressive Model with Non-Gaussian Structure; 3.1 The VAR Model with Non-Gaussian Structure; 4 Real Data Analysis; 4.1 Model 1; 4.2 Model 2; 5 Conclusions; References; Imputation of Missing Observations for Heavy Tailed Cyclostationary Time Series; 1 Introduction; 2 Estimation of the Model Parameters; 3 Simulation Study; 4 Conclusions; References
5 ConclusionReferences; Damage Assessment of Rolling Element Bearing Using Cyclostationary Processing of AE Signals with Electromagnetic Interference; 1 Introduction; 2 Problem Description; 3 Experimental Set-up; 4 Results; 5 Conclusion; References; The Stochastic Recurrence Structure of Geophysical Phenomena; 1 Introduction; 2 Annual Variation of Geophysical Processes; 3 Daily Variation; 4 The Properties of Annual and Daily Characteristic Estimators; 5 Conclusions; References; Influence of Different Signal Characteristics on PAR Model Stability; 1 Introduction
2 Periodic Autoregressive (PAR) Model2.1 Non-Gaussian Noise; 3 Motivation; 4 Influence of Non-Gaussian Noise to PAR Estimation; 4.1 Methodology; 4.2 Simulation Results; 5 Influence to PAR Estimation for Different Number of Period Repetitions; 5.1 Methodology; 5.2 Simulations; 6 Conclusions; References; Limiting Distributions for Explosive PAR(1) Time Series with Strongly Mixing Innovation; 1 Introduction; 2 Background : PAR(1) Time Series; 3 Explosive Asymptotic Behaviour of the Model; 4 Least Squares Estimation of the Coefficients; 5 Estimation of φ; 6 Simulation; References
PARMA Models with Applications in R1 Introduction; 2 PARMA Time Series Analysis; 2.1 Identification of PC-T Structure; 2.2 Estimation of PARMA Parameters; 2.3 Goodness of Fit and Model Selection; 3 Real Data Example; 3.1 Data; 3.2 Non-parametric Spectral Analysis; 3.3 Preliminary Identification and Conditioning; 3.4 Identification; 3.5 Model Fitting; 3.6 Short Time Prediction for PAR Models; 4 Simulated Data Example; 5 Conclusions; References; Multidimensional Analysis of New Zealand Electricity Prices; 1 Introduction; 2 Main Features of New Zealand Electricity Prices
2.1 New Zealand Electricity Market2.2 Relationship Between Respective Price Data Corresponding to Analysed Nodes; 2.3 Relationship Between Price Data and Deterministic Factors; 3 Multivariate Autoregressive Model with Non-Gaussian Structure; 3.1 The VAR Model with Non-Gaussian Structure; 4 Real Data Analysis; 4.1 Model 1; 4.2 Model 2; 5 Conclusions; References; Imputation of Missing Observations for Heavy Tailed Cyclostationary Time Series; 1 Introduction; 2 Estimation of the Model Parameters; 3 Simulation Study; 4 Conclusions; References