first-order autoregressive parameter
Estimation for Nonnegative First Order Autoregressive Processes with an Unknown Location Parameter
... the autoregressive coefficient in the causal AR(1) process is estimated by taking the mini- mum of the ratio of two sample values while estimation for the unknown location parameter was achieved through ...
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Statistical inference for first order random coefficient integer valued autoregressive processes
... Zheng et al. [] also generalized the above model to a pth-order model. For model (.), Zheng et al. [] established the ergodicity and derived the conditional least-squares and quasi-likelihood estimators of ...
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First-Order Fractionally Integrated Non-Separable Spatial Autoregressive (FINSSAR(1,1)) Model and Some of its Properties
... We simulated the FINSSAR(1,1) process in two stages. First the two dimensional white noise { Z ij } was generated and by using equation (6) we obtained { W ij } . Then { } Y ij was obtained by using equation (5). ...
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Subject specific and population average models for binary longitudinal data: a tutorial
... (Exch), first-order autoregressive (AR1) and unstructured (Uns) correlation ...model parameter, the parameter estimate and (robust) standard ...
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Finite sample criteria for autoregressive model order selection
... AR order selection criteria, designed for the finite sample case, are introduced by Broersen and Wensink [21, ...The first criterion is the finite sample criterion (FSC) [21], which gives an estimate of the ...
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A Bayesian latent process spatiotemporal regression model for areal count data
... the first-order autoregressive latent process as against its the error covariance matrix was ...matrix. Parameter estimation in the proposed models is shown to be straightforward and we have ...
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Change Point Estimation of Location Parameter in Multistage Processes
... A first order autoregressive model (AR(1)) is used to model a multistage process observations, where a X -chart is established for monitoring its ...location parameter of the ...in ...
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The First Order Autoregressive Model with Coefficient Contains Non Negative Random Elements: Simulation and Esimation
... The RCA models have been studied by several authors [1-3]. Most of their theoreic properties are well-known, including conditions for the existence and the uniqueness of a stationary solution, or for the existence of ...
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Application of Quantitative Forecasting Models in a Manufacturing Industry
... the first step of this ...the order of the consecutive and seasonal differencing required to make series stationary, as well as specifying the order of the regular and seasonal auto regressive and ...
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Step Change Point Estimation of the First-order Autoregressive Autocorrelated Simple Linear Profiles
... In this paper, we proposed a new estimator to estimate the step change point in Phase II monitoring of AR(1) autocorrelated simple linear proles when the auto- correlation structure of the observations within each prole ...
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Alternative GMM Estimators for First order Autoregressive Panel Model: An Improving Efficiency Approach
... When dynamic models are estimated using panel data, the usual least squares methods lead to inconsistent estimates of the parameters of the models when the time dimension ( ) is short regardless of the cross sectional ...
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Bayesian Inference in Spatial Sample Selection Models
... a first order spatial autoregressive process in the disturbance ...a first order spatial autoregressive process in the disturbance ...the parameter of the outcome ...
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Order Selection of Spatial and Temporal Autoregressive Models with Errors in Variables
... model order selection for processes observed with additive Gaussian ...noisy autoregressive models and provide an estimator that takes care of the observational ...
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Noncausal autoregressions for economic time series
... causal autoregressive model by least squares or Gaussian ML and determine its or- der by using conventional procedures such as diagnostic checks and model selection ...selected order are then estimated and ...
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Multiple Positive Solutions for Nonlinear First Order Impulsive Dynamic Equations on Time Scales with Parameter
... By using the Leggett-Williams fixed point theorem, the existence of three positive solutions to a class of nonlinear first-order periodic boundary value problems of impulsive dynamic equations on time ...
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Using a variance-based sensitivity analysis for analyzing the relation between measurements and unknown parameters of a physical model
... The study of uncertainty is usually composed of two re- lated activities referred as uncertainty analysis and sensitivity analysis. Uncertainty analysis aims quantifying the overall uncertainty associated with the ...
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Multi-parameter, impulsive effects and positive periodic solutions of first-order functional differential equations
... new and more general existence and multiplicity results are derived in terms of different values of λ > 0 and μ > 0. Here we not only consider the case that g is bounded, but the case that g is not necessarily ...
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Sequential Parameter Estimation of Time Varying Non Gaussian Autoregressive Processes
... One advantage of particle filters over other methods is that they can be applied to almost any type of problem where signal variations are present. This includes models with high nonlinearities and with noises that are ...
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The effect of autocorrelation on the performance of MEWMA control chart with controlled correlation
... of order q, ∇ is a backward difference operator, B is the backshift operator, and 𝜖 is a sequence of normally and independently distributed random shock with mean zero and constant variance 𝜎 ...
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A Parameter-Uniform Essentially First Order Convergent Fitted Mesh Method for a Singularly Perturbed Robin Problem
... second order ordinary differential equations of reaction-diffusion type with Robin boundary conditions is ...essentially first order convergent uniformly with respect to all of the ...
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