Browsing by Subject "Time series"
Now showing items 2135 of 35

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Ksample subsampling in general spaces: The case of independent time series
(2010)The problem of subsampling in twosample and Ksample settings is addressed where both the data and the statistics of interest take values in general spaces. We focus on the case where each sample is a stationary time ...

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Likelihood Estimation for the INAR(p) Model by Saddlepoint Approximation
(2015)Saddlepoint techniques have been used successfully in many applications, owing to the high accuracy with which they can approximate intractable densities and tail probabilities. This article concerns their use for the ...

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Modelling interventions in INGARCH processes
(2016)We study different approaches for modelling intervention effects in time series of counts, focusing on the socalled integervalued GARCH models. A previous study treated a model where an intervention affects the nonobservable ...

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Nonparametric resampling for homogeneous strong mixing random fields
(1993)Künsch (1989, Ann. Statist.17 12171241) and Liu ane Singh (1992, in Exploring Limits of Bootstrap (R. Le Page and L. Billard, Eds.), pp. 225248, Wiley, New York) have recently introduced a block resampling method that ...

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Particulate matter concentrations during desert dust outbreaks and daily mortality in Nicosia, Cyprus
(2013)Ambient particulate matter (PM) has been shown to have short and longterm effects on cardiorespiratory mortality and morbidity. Most of the risk is associated with fine PM (PM 2.5); however, recent evidence suggests that ...

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Regression models with mixed sampling frequencies
(2010)We study regression models that involve data sampled at different frequencies. We derive the asymptotic properties of the NLS estimators of such regression models and compare them with the LS estimators of a traditional ...

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Article
Shortterm load forecasting: The similar shape functional timeseries predictor
(2013)A novel functional timeseries methodology for shortterm load forecasting is introduced. The prediction is performed by means of a weighted average of past daily load segments, the shape of which is similar to the expected ...

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Spectral density ratio based clustering methods for the binary segmentation of protein sequences: A comparative study
(2010)We compare several spectral domain based clustering methods for partitioning protein sequence data. The main instrument for this exercise is the spectral density ratio model, which specifies that the logarithmic ratio of ...

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Spectral estimation
(2010)Wereview spectral analysis and its application in inference for stationary processes. As can be seen from the list of references, the practice of spectral analysis is widespread in diverse scientific and engineering fields, ...

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Subsampling confidence intervals for parameters of atmospheric time series: Block size choice and calibration
(2005)Problems of practical implementation of the computer intensive subsampling methodology are addressed by Monte Carlo simulations of a situation typical for atmospheric time series. The motivating data were collected under ...

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Subsampling for heteroskedastic time series
(1997)In this article, a general theory for the construction of confidence intervals or regions in the context of heteroskedasticdependent data is presented. The basic idea is to approximate the sampling distribution of a ...

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Tapered block bootstrap
(2001)We introduce and study tapered block bootstrap methodology that yields an improvement over the wellknown block bootstrap for time series of Künsch (1989). The asymptotic validity and the favourable bias properties of the ...

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Testing Time Series Linearity. Traditional and Bootstrap Methods
(2012)We review the notion of time series linearity and describe recent advances in linearity and Gaussianity testing via data resampling methodologies. Many advances have been made since the first published tests of linearity ...

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Valid resampling of higherorder statistics using the linear process bootstrap and autoregressive sieve bootstrap
(2013)We show that the linear process bootstrap (LPB) and the autoregressive sieve bootstrap (AR sieve) are, in general, not valid for statistics whose largesample distribution depends on moments of order higher than two, ...