Results 31 to 40 of about 1,135 (106)
Ingeniería y Ciencia, 2012 Muchas series de tiempo con tendencia y ciclos estacionales son exitosamente modeladas y pronosticadas usando el modelo airline de Box y Jenkins; sin embargo, la presencia de no linealidades en los datos son despreciadas por este modelo. En este artículo,
J D Velásquez, C J Franco
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Geoestadística aplicada a series de tiempo autorregresivas: un estudio de simulación
Revista Integración, 2017 La geoestadística puede usarse como método de predicción de datos faltantes en series temporales. El procedimiento se basa en el estudio de la estructura de autocorrelación temporal de la serie de tiempo por medio de la función de variograma, que es ...
Ramón Giraldo +2 more
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Ingeniería y Ciencia, 2015 En este trabajo se identificó un modelo en series de tiempo para el control de la tasa de penetración (ROP) en un pozo de referencia denominado V∗∗∗ que pertenece al campo en desarrollo VEL que está ubicado en la cuenca del Valle del Magdalena Medio (VMM)
Henry Daniel Hernández Martínez +1 more
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On prediction errors in regression models with nonstationary regressors
, 2006 In this article asymptotic expressions for the final prediction error (FPE) and the accumulated prediction error (APE) of the least squares predictor are obtained in regression models with nonstationary regressors. It is shown that the term of order $1/n$
Ing, Ching-Kang, Sin, Chor-Yiu
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Dependent Lindeberg central limit theorem and some applications [PDF]
, 2007 In this paper, a very useful lemma (in two versions) is proved: it simplifies notably the essential step to establish a Lindeberg central limit theorem for dependent processes. Then, applying this lemma to weakly dependent processes introduced in Doukhan
Bardet, Jean-Marc +3 more
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Multivariate volatility models
, 2006 Correlations between asset returns are important in many financial applications. In recent years, multivariate volatility models have been used to describe the time-varying feature of the correlations. However, the curse of dimensionality quickly becomes
Tsay, Ruey S.
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A Bayesian Networks Approach to Operational Risk
, 2010 A system for Operational Risk management based on the computational paradigm of Bayesian Networks is presented. The algorithm allows the construction of a Bayesian Network targeted for each bank using only internal loss data, and takes into account in a ...
Aquaro, V. +5 more
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Single proxy synthetic control
Journal of Causal InferenceSynthetic control methods are widely used to estimate the treatment effect on a single treated unit in time-series settings. A common approach to estimate synthetic control weights is to regress the treated unit’s pretreatment outcome and covariates ...
Park Chan, Tchetgen Tchetgen Eric J.
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Journal of Causal InferenceTime-dependent coarse structural nested mean models (coarse SNMMs) were developed to estimate treatment effects from longitudinal observational data. Coarse SNMMs estimate the combined effect of multiple treatment dosages and are thus useful to estimate ...
Lok Judith J.
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Modeling macroeconomic time series via heavy tailed distributions
, 2007 It has been shown that some macroeconomic time series, especially those where outliers could be present, can be well modelled using heavy tailed distributions for the noise components.
Aston, J. A. D.
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