185,693 research outputs found
Nonparametric survival analysis of epidemic data
This paper develops nonparametric methods for the survival analysis of
epidemic data based on contact intervals. The contact interval from person i to
person j is the time between the onset of infectiousness in i and infectious
contact from i to j, where we define infectious contact as a contact sufficient
to infect a susceptible individual. We show that the Nelson-Aalen estimator
produces an unbiased estimate of the contact interval cumulative hazard
function when who-infects-whom is observed. When who-infects-whom is not
observed, we average the Nelson-Aalen estimates from all transmission networks
consistent with the observed data using an EM algorithm. This converges to a
nonparametric MLE of the contact interval cumulative hazard function that we
call the marginal Nelson-Aalen estimate. We study the behavior of these methods
in simulations and use them to analyze household surveillance data from the
2009 influenza A(H1N1) pandemic. In an appendix, we show that these methods
extend chain-binomial models to continuous time.Comment: 30 pages, 6 figure
Limit Laws in Transaction-Level Asset Price Models
We consider pure-jump transaction-level models for asset prices in continuous
time, driven by point processes. In a bivariate model that admits
cointegration, we allow for time deformations to account for such effects as
intraday seasonal patterns in volatility, and non-trading periods that may be
different for the two assets. We also allow for asymmetries (leverage effects).
We obtain the asymptotic distribution of the log-price process. We also obtain
the asymptotic distribution of the ordinary least-squares estimator of the
cointegrating parameter based on data sampled from an equally-spaced
discretization of calendar time, in the case of weak fractional cointegration.
For this same case, we obtain the asymptotic distribution for a tapered
estimator under moreComment: This version accepted by Econometric Theor
Point patterns occurring on complex structures in space and space-time: An alternative network approach
This paper presents an alternative approach of analyzing possibly multitype
point patterns in space and space-time that occur on network structures, and
introduces several different graph-related intensity measures. The proposed
formalism allows to control for processes on undirected, directional as well as
partially directed network structures and is not restricted to linearity or
circularity
A Simple Test for the Absence of Covariate Dependence in Hazard Regression Models
This paper extends commonly used tests for equality of hazard rates in a two-sample or k-sample setup to a situation where the covariate under study is continuous. In other words, we test the hypothesis that the conditional hazard rate is the same for all covariate values, against the omnibus alternative as well as more specific alternatives, when the covariate is continuous. The tests developed are particularly useful for
detecting trend in the underlying conditional hazard rates or changepoint trend alternatives. Asymptotic distribution of the test statistics are established and small sample properties of the tests are studied. An application to the e¤ect of aggregate Q on corporate failure in the UK shows evidence of trend in the covariate e¤ect, whereas a Cox regression model failed to detect evidence of any covariate effect. Finally, we discuss an
important extension to testing for proportionality of hazards in the presence of individual level frailty with arbitrary distribution
Seeking for a fingerprint: analysis of point processes in actigraphy recording
Motor activity of humans displays complex temporal fluctuations which can be
characterized by scale-invariant statistics, thus documenting that structure
and fluctuations of such kinetics remain similar over a broad range of time
scales. Former studies on humans regularly deprived of sleep or suffering from
sleep disorders predicted change in the invariant scale parameters with respect
to those representative for healthy subjects. In this study we investigate the
signal patterns from actigraphy recordings by means of characteristic measures
of fractional point processes. We analyse spontaneous locomotor activity of
healthy individuals recorded during a week of regular sleep and a week of
chronic partial sleep deprivation. Behavioural symptoms of lack of sleep can be
evaluated by analysing statistics of duration times during active and resting
states, and alteration of behavioural organization can be assessed by analysis
of power laws detected in the event count distribution, distribution of waiting
times between consecutive movements and detrended fluctuation analysis of
recorded time series. We claim that among different measures characterizing
complexity of the actigraphy recordings and their variations implied by chronic
sleep distress, the exponents characterizing slopes of survival functions in
resting states are the most effective biomarkers distinguishing between healthy
and sleep-deprived groups.Comment: Communicated at UPON2015, 14-17 July 2015, Barcelona. 21 pages, 11
figures; updated: figures 4-7, text revised, expanded Sec. 1,3,
Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL
We develop a model in which interactions between nodes of a dynamic network
are counted by non homogeneous Poisson processes. In a block modelling
perspective, nodes belong to hidden clusters (whose number is unknown) and the
intensity functions of the counting processes only depend on the clusters of
nodes. In order to make inference tractable we move to discrete time by
partitioning the entire time horizon in which interactions are observed in
fixed-length time sub-intervals. First, we derive an exact integrated
classification likelihood criterion and maximize it relying on a greedy search
approach. This allows to estimate the memberships to clusters and the number of
clusters simultaneously. Then a maximum-likelihood estimator is developed to
estimate non parametrically the integrated intensities. We discuss the
over-fitting problems of the model and propose a regularized version solving
these issues. Experiments on real and simulated data are carried out in order
to assess the proposed methodology
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