Predicting seasonal influenza transmission using functional regression models with temporal dependence.

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Predicting seasonal influenza transmission using functional regression models with temporal dependence.

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2018 nî lūn-bûn

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2018年の論文

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年学术文章

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2018年學術文章

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2018年學術文章

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2018年學術文章

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Predicting seasonal influenza ...... dels with temporal dependence.

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Predicting seasonal influenza ...... dels with temporal dependence.

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label

Predicting seasonal influenza ...... dels with temporal dependence.

@en

Predicting seasonal influenza ...... dels with temporal dependence.

@nl

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Predicting seasonal influenza ...... dels with temporal dependence.

@en

Predicting seasonal influenza ...... dels with temporal dependence.

@nl

P1476

Predicting seasonal influenza ...... dels with temporal dependence.

@en

P2093

Manuel Febrero-Bande

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María Pilar Muñoz

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Àngela Domínguez

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P2860

An introduction with medical applications to functional data analysis.

Mortality due to influenza in the United States--an annualized regression approach using multiple-cause mortality data.

Influenza activity in Europe during eight seasons (1999-2007): an evaluation of the indicators used to measure activity and an assessment of the timing, length and course of peak activity (spread) across Europe.

Zanamivir prophylaxis: an effective strategy for the prevention of influenza types A and B within households.

An evaluation of influenza mortality surveillance, 1962-1979. I. Time series forecasts of expected pneumonia and influenza deaths.

Survival of airborne influenza virus: effects of propagating host, relative humidity, and composition of spray fluids.

Bayesian hierarchical Poisson models with a hidden Markov structure for the detection of influenza epidemic outbreaks.

Predictive assessment of a non-linear random effects model for multivariate time series of infectious disease counts.

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e0194250

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scholarly article

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10.1371/JOURNAL.PONE.0194250

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English

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P478

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Manuel Oviedo de la Fuente

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2018-04-25T00:00:00Z

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29694350

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5918942

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