eHabitat: A Contribution to the Model Web for Habitat Assessments and Ecological Forecasting

By D. Gregoire, Skoien Jon, Mendes De Jesus Jorge Samuel, Peedell Stephen, A. Hartley, Nativi Stefano, S. Mattia, Geller Gary. 2011

366 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/b4372eb88e27c65fc0c5792b1911bd90b5854dea

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Citations in the corpus

The response of interest rates to U.S. and U.K. quantitative easing (2012, methodology): “6 See GRRS and JLST and further discussion below.”
A spot market model for pricing derivatives in electricity markets (2004, unknown): “For details about the Kalman filtering algorithm, see [16].”
Stochastic model specification search for Gaussian and partial non-Gaussian state space models (2010, methodology): “We reconsider the series of UK coal consumption, analyzed in Harvey (1989), FrühwirthSchnatter (1994) and Frühwirth-Schnatter (1995), among others.”
A NON‐GAUSSIAN FAMILY OF STATE‐SPACE MODELS WITH EXACT MARGINAL LIKELIHOOD (2013, unknown): “The MLE is calculated through the well-known Broyden–Fletcher–Goldfarb–Shanno algorithm (Nocedal and Wright, 2006), and the confidence intervals are built using numerical derivatives to obtain the Fisher information matrix, as in Franco et al. (2008). wileyonlinelibrary.com/journal/jtsa Copyright © ”
Forecasting Random Walks Under Drift Instability (2008, unknown): “A number of time-varying parameter models have been considered in the forecasting literature in which the unknown parameters are assumed to follow random walks, see, for example, Harvey (1989).”
Online Context-Aware Recommendation with Time Varying Multi-Armed Bandit (2016, methodology): “We apply the Kalman filtering [13] method to recursively update the sufficient statistics for ηk,t based on the new observation and the sufficient statistics at time t − 1.”
Psychotherapy in 2022: A Delphi poll on its future. (2013, background): “The accuracy of probability forecasts increases over Delphi rounds, up to the second round (Martino, 1972; Ascher, 1978), and when statistical summaries are provided to the experts (Rowe, Wright, & McColl, 2005).”
Bootstrap LR tests of stationarity, common trends and cointegration (2012, unknown): “The model is sometimes known as the ‘local level model’and it is thoroughly analysed in [20,21], inter alia.”
A protocol for data exploration to avoid common statistical problems (2010, methodology): “These include using lagged response variables as covariates (Brockwell & Davis 2002), mixed effects modelling (Pinheiro & Bates 2000), imposing a residual correlation structure using generalized least squares (Zuur et al. 2009a) or allowing regression parameters to change over time (Harvey 1989).”
A meta-analysis of international tourism demand forecasting and implications for practice (2014, methodology): “Exogenous variables can be included in BSM to form a structural time series model (STSM) with explanatory variables (Harvey, 1990; Gonzalez & Moral, 1995).”
A Review of Some Modern Approaches to the Problem of Trend Extraction (2012, methodology): “The Structural approach (Harvey, 1989) on the other hand also uses maximum likelihood estimation, but the form of the likelihood is dictated by a pre-specified model form for the components.”
Convergence of European spot market prices for natural gas? A real-time analysis of market integration using the Kalman Filter (2006, background): “3 For a formal description see Harvey (1989) and Meinhold and Singpurwalla (1983). less than 6 euros per MWh; on the contrary, the minimum for the UK is 1.86 Euros/MWh.”
TREND ESTIMATION AND THE HODRICK-PRESCOTT FILTER (2008, unknown): “The statistical treatment of such unobserved component models is based on the state space form (SSF), as described in Harvey (1989) and Kitagawa and Gersch (1996).”
Measuring the Natural Rate of Interest: International Trends and Determinants (2016, methodology): “…values of λg from the first step and λz from the second step and estimate the remaining model parameters by maximum likelihood as described by Harvey (1989).6 Throughout, we impose the constraints that the slope ar of the IS equation is negative and the slope by of the Phillips curve is…”