[PDF] Top 20 Fixed and random coefficient time series
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Fixed and random coefficient time series
... for time series, most of these classes requiring a detailed knowledge of the form of the ...by time series ...a time series by the usual linear ... See full document
153
Concepts and tools for nonlinear time series modelling
... Tweedie, Random Coefficient Autoregressive Processes: a Markov Chain Analysis of Stationarity and Finiteness of Moments, Journal of Time Series Analysis, 6 1985 1–14.. Findley, The overf[r] ... See full document
64
Bayesian analysis of random coefficient autoregressive models
... also investigated the performance of the model selection criteria using simulation studies. It appears that both AIC and GGC performs well in picking up the correct model. In general we find that RCAR models are robust ... See full document
35
Sensitivity of Lagrangian Particle Tracking Based on a 3D Numerical Model
... for random movement of particle: horizontal only; vertical only; both horizontal and vertical (full 3D) and without random ...a fixed depth under water surface is also ... See full document
7
Belief Propagation for Continuous State Spaces: Stochastic Message-Passing with Quantitative Guarantees
... orthogonal series message-passing (SOSMP), for computing the BP fixed point in models with continuous random ...orthogonal series basis expansion, and a stochastic estimation of the basis ... See full document
37
Estimation for random coefficient integer valued autoregressive model under random environment
... a random coeffi- cient model, in which the fixed autoregressive parameter was replaced by the random variable, and derived conditional least squares and quasi-likelihood estimators of the pro- posed model ... See full document
16
Residual uncertainty estimation using instance based learning with applications to hydrologic forecasting
... generate random sequences of daily weather variables (Rajagopalan and Lall, ...temperature series for the Columbia River ...a fixed time series of input and fixed model ... See full document
16
Statistical inference in a random coefficient panel model
... a time series context, to work well in comparison with the maximum likelihood approach (Schick, 1996; Koul and Schick, ...the time series case, the suitably normalised WLS estimator converges ... See full document
46
Estimation and inference in mixed fixed and random coefficient panel data models
... both fixed and random coefficients, as well as the variance components, in a wide class of heterogeneous ...the random coefficient covariance without running into the problem of negative ... See full document
55
Explaining Fixed Effects: Random Effects modelling of Time-Series Cross-Sectional and Panel Data
... The technical problems of analyzing hierarchies in data are well known. Put briefly, standard ‘pooled’ linear regression models assume that residuals are independently and identically distributed. That is, once all ... See full document
39
Determining the verse of magnetic turbulent cascades in the Earth’s
... the time series col- lected along the POLAR trajectory and treating them as prob- abilistic evolutions we are not looking at the single direct or inverse cascade event of “eddies” crumbling or coalescing: ... See full document
9
Non-Linear Time Series Modelling with Applications to Equity and Fixed Income Markets
... larly interesting and they have been extensively used in the existing empirical literature. These models are straightforward generalizations of linear models. For example, the sim- ple two regime Threshold Autoregressive ... See full document
131
Fixed Point Theorems for Random Lowersemi-continuous Mappings
... latter condition is related to a condition that was originally introduced by Petryshyn 1 for single-valued operators, in order to prove existence of fixed points. However, in our case, the condition is used to ... See full document
7
General Theory of Antithetic Time Series
... Of the terms p, λ , and ω , only p is unique to antithetic time series analysis, and it is not a fitted parameter. When implemented, p is actually a constant set to − 0.001 , an approximation of 0 − . Also, ... See full document
16
A simple approach to inference in random coefficient models
... Carter and Yang (1986) derived the asymptotic distribution of the estimated generalized least squares estimator as either n, the number of experimental units, tends to infinity and/or as[r] ... See full document
27
Common random fixed point results with application to a system of nonlinear integral equations
... Remark 2.4. If X is a separable Banach space then the σ −algebra generated by the class of all spherical neighour- hoods of X is equal to the σ−algebra of Borel subsets of X . Hence every strong and also weak ... See full document
8
Application of random fixed point theorems in solving nonlinear stochastic integral equation of the Hammerstein type
... mappings. Random fixed point theorems with an application to Random differential equations in Banach spaces are obtained by Itoh ...several random fixed point theorems including ... See full document
6
Trade openness, capital openness and government size
... Portfolio openness has also a statistically significant negative coefficient when fixed effects are used, becoming significant only at 10 per cent level when switching to random effects.[r] ... See full document
28
Sequential point and interval estimation of scale parameter of exponential distribution
... Here we derive exact expressions for the stopping time and confidence coefficient of the fixed-width interval estimation procedure and for the stopping time associted with point estimati[r] ... See full document
8
On the Quantum Zeno Effect and Time Series Related to Quantum Measurements
... its time evolution one has to perform sev- eral EEG measurements at different ...that time series, ...the time evolution of the configuration of excited neurons in the ... See full document
9
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