Generalized Autoregressive Moving Average Models

By Michael A. Benjamin, Robert A. Rigby, D. Stasinopoulos. 2003

359 citations recorded by the source corpus.

Subfields: Finance, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/bf70989a2ae3bc8083ef7daafe25dcdf08504c53

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Citations in the corpus

Kumaraswamy autoregressive moving average models for double bounded environmental data (2017, methodology): “In order to define the proposed model, we shall follow similar construction as the generalized autoregressive and moving average model (GARMA) (Benjamin et al., 2003) and the beta autoregressive and moving average model (βARMA) (Rocha and Cribari-Neto, 2009), but we shall employ a parametrization…”
Vector Multiplicative Error Models: Representation and Inference (2006, methodology): “5 We adapt the formulation of Benjamin et al. (2003) to this work.”
A negative binomial model for time series of counts (2009, methodology): “For parameter estimation we adopted the approach of Benjamin et al. (2003), maximizing the likelihood L(β, r ) with respect to β for different r values.”
Binomial Autoregressive Moving Average Models With an Application to U.S. Recessions (2008, methodology): “See Benjamin, Rigby, and Stasinopoulos 2003 for the introduction of GARMA models, as well as a review of the literature.)”
Count Time Series Models (2012, background): “(2000), Kedem and Fokianos (2002), Benjamin et al. (2003), Davis et al. (2003), Fokianos and Kedem (2004), Jung et al. (2006), Creal et al. (2008) and Fokianos and Tjøstheim (2011). Suppose again that {Yt} denotes a count time series.”
A negative binomial integer‐valued GARCH model (2011, methodology): “We also consider the normalized conditional randomized quantile residuals of Dunn and Smyth (1996) and Benjamin et al. (2003).”
GENERALIZED AUTOREGRESSIVE SCORE MODELS WITH APPLICATIONS (2013, methodology): “…family of distributions) the generalized linear autoregressive (GLAR) models of Shephard (1995), the generalized autoregressive moving average (GARMA) models of Benjamin, Rigby, and Stanispoulos (2003), and the vector multiplicative error models (MEM) of Cipollini, Engle, and Gallo (2006).”
Partial Likelihood Inference For Time Series Following Generalized Linear Models (2004, background): “…(5) has been termed generalized linear autoregressive moving average (Shephard, 1995), GLARMA(p, q), or generalized autoregressive moving average (Benjamin et al., 2003), GARMA(p, q), of order (p, q), respectively, since it generalizes the common autoregressive and moving average models by…”
A General Framework for Observation Driven Time-Varying Parameter Models (2008, neutral): “Shephard (1995) and Benjamin et al. (2003) proposed parameter-driven models for other distributions in this family.”
Discrete-valued ARMA processes (2009, methodology): “Instead, we may use the odds ratio association in the case of categorical time series for the serial dependence (Agresti, 2002).”
Generalized additive models for location, scale and shape (2005, methodology): “In the derivative fitting method, the derivatives of a predictor ηk with respect to non-linear parameters are included in the design matrix Xk in the fitting algorithm; see, for example, Benjamin et al. (2003).”
Beta autoregressive moving average models (2009, background): “where β = (β1 ,...,β k) � is a set of unknown linear parameters and τt is an ARMA component which shall be described below and is similar to what is given in Benjamin et al. (2003) .”