AR(1) model
Asymptotic Inference for the Weak Stationary Double AR(1) Model
... An AR(1) model with ARCH(1) error structure is known as the first-order double autoregressive (DAR(1)) model. In this paper, a conditional likelihood based method is proposed to ...
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Asymptotic Inferences for an AR(1) Model with a Change Point: Stationary and Nearly Non stationary Cases
... in AR(1) model was first independently studied by Chan and Wei (1987) and Phillips ...stationary AR(1) model and unit root ...
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Edgeworth Approximation of a Finite Sample Distribution for an AR(1) Model with Measurement Error
... the AR(1) model is not ...an AR model with measurement errors in [4] and statistical a test for the existence of noise is proposed in ...
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A further look at Modified ML estimation of the panel AR(1) model with fixed effects and arbitrary initial conditions
... panel AR(1) model with …xed e¤ects and arbitrary initial conditions and possibly covariates when the time di- mension, T , is ...= 1; the limiting modi…ed pro…le log-likelihood function for ...
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Influential Observations in Stochastic Model of Divisia Index Numbers with AR(1) Errors
... mean model and regression through the origin model with AR(1) ...regression model with more than one regressors in the presence and absence of constant ...regression model with ...
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The application of game-based AR learning model in English sentence learning
... applying AR technology in English vocabularies learning in primary school or kindergarten (Koutromanos, Sofos & Avraamidou, ...an AR English vocabularies learning system for kindergarten ...how ...
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Diagnostic Measures in Ridge Regression Model with AR(1) Errors under the Stochastic Linear Restrictions
... mean-shift model for detecting outliers in case of ridge regression model in the presence of stochastic linear restrictions when the error terms follow by an autoregressive AR(1) ...outlier ...
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A Fault Diagnosis Approach for Gears Based on IMF AR Model and SVM
... accurate AR model can reflect the characteristics of a dynamic ...of AR model are very sensitive to the condition variation [9, ...whereas AR model can model transients ...
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Sup tests for linearity in a general nonlinear AR(1) model when the supremum is taken over the full parameter space
... series model of order 1, involving a nonnegative nuisance parameter which (i) is not identified under the null hypothesis and (ii) gives the linear model when equal to ...
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Asymptotic normality of Huber Dutter estimators in a linear EV model with AR(1) processes
... The paper discusses the models (.)-(.) with a robust approach, which has been sug- gested by Huber and Dutter. We extend some results of Hu [], Silvapullé [], etc. to the EV regression model with ...
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Random walk analysis with multiple structural breaks: Case study in emerging market of S&P BSE sectoral indices stocks
... switching AR (1) model which has effectively predicted the frequent changes in the variance as well as in the mean between the regions for all the sectors in the given ...
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Perturbation analysis in non-stationary ar(1) time series
... autoregressive model AR(1) is often used for prediction in ...This model is non-stationary if it has a unit ...− 1 and ...root AR(1) ...
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On the evolution of pre-flare patterns of a 3-dimensional model of AR 11429
... permeability of free space. This approximation may be a good one for describing the state of the coronal magnetic field. However, many studies claim (for good reasons) that the FF approximation is not reliable below the ...
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Comparison of νμ Ar multiplicity distributions observed by MicroBooNE to GENIE model predictions
... The MicroBooNE detector lacks appreciable shielding from cosmic rays (CR) since the detector is at the earth’s surface and has little overburden. Most events that are recorded and processed through an online software ...
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Structural change in non stationary AR(1) models
... root model was first studied by Phillips (1987) and Chan and Wei (1987) ...ary AR(1) model and the unit root ...local-to-unity AR(1) ...the AR parameter for the following ...
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Measuring the Core Inflation in Turkey with the SM AR Model
... + 1) ♠❛tr✐① ♦❢ ♦❜s❡r✈❛t✐♦♥s ✇❤❡r❡ y ✐s t❤❡ N × 1 ✈❡❝✲ t♦r ♦❢ ♦❜s❡r✈❛t✐♦♥s ♦♥ t❤❡ r❡s♣♦♥s❡ ✈❛r✐❛❜❧❡ ❛♥❞ X ✐s t❤❡ N × K ♠❛tr✐① ♦❢ ♦❜s❡r✈❛t✐♦♥s ♦♥ t❤❡ ❡①♣❧❛♥❛t♦r② ✈❛r✐❛❜❧❡s✳ ❲❡ r❡♠♦✈❡ ♦❜s❡r✈❛t✐♦♥ i ❢r♦♠ Z ...
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Forecasting Macedonian GDP: Evaluation of different models for short term forecasting
... GDP: 1) ARIMA model; 2) AR model estimated by the Kalman filter; 3) model that explains Macedonian GDP as a function of the foreign demand; 4) small structural model that links ...
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Bootstrap and multiple imputation under missing data in AR(1) models
... When one or more observations are missing it may be necessary to estimate the model and also to obtain estimates of the missing values. By including estimates of missing values, a better understanding of the ...
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Numerical Approximations of Average Run Length for AR(1) on Exponential CUSUM
... In this article, we study the ARLs of the CUSUM procedure when observations are from a first order autoregressive model with exponential white noise. We derive integral equations for the ARLs and then solve the ...
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Monitoring and Change Point Estimation of AR(1) Autocorrelated Polynomial Profiles
... In this paper, the problem of monitoring autocorrelated polynomial profiles is addressed in which the relationship between a response and a single explanatory variable is defined by a k th order polynomial regression, ...
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