1,303 research outputs found
Optimal detection of changepoints with a linear computational cost
We consider the problem of detecting multiple changepoints in large data
sets. Our focus is on applications where the number of changepoints will
increase as we collect more data: for example in genetics as we analyse larger
regions of the genome, or in finance as we observe time-series over longer
periods. We consider the common approach of detecting changepoints through
minimising a cost function over possible numbers and locations of changepoints.
This includes several established procedures for detecting changing points,
such as penalised likelihood and minimum description length. We introduce a new
method for finding the minimum of such cost functions and hence the optimal
number and location of changepoints that has a computational cost which, under
mild conditions, is linear in the number of observations. This compares
favourably with existing methods for the same problem whose computational cost
can be quadratic or even cubic. In simulation studies we show that our new
method can be orders of magnitude faster than these alternative exact methods.
We also compare with the Binary Segmentation algorithm for identifying
changepoints, showing that the exactness of our approach can lead to
substantial improvements in the accuracy of the inferred segmentation of the
data.Comment: 25 pages, 4 figures, To appear in Journal of the American Statistical
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Medieval property investors, ca. 1300-1500
This paper utilises a dataset of freehold land and property transactions from medieval England to highlight the growing commercialisation of the economy. By drawing on the legal records we are able to demonstrate that the medieval real estate market provided the opportunity for investors to profit. Careful analysis of the data provides evidence of group purchases, multiple transactions and investors buying outside of their own locality. The identification of these ‘investors’ and their buying behaviours, set within the context of the English medieval economy, contributes to the early commercialisation debate
Water utilization, evapotranspiration and soil moisture monitoring in the south east region of south Australia
There are no author-identified significant results in this report
Didilia ooglypta n.gen., n.sp. (Tetradonematidae : Mermithoidea : Nematoda), a parasite of phlebotomine sandflies in Afghanistan
An algorithm for satellite-based burned area mapping using change point detection and Markov random fields
The local partial autocorrelation function and some applications
The classical regular and partial autocorrelation functions are powerful tools for stationary time series modelling and analysis. However, it is increasingly recognized that many time series are not stationary and the use of classical global autocorrelations can give misleading answers. This article introduces two estimators of the local partial autocorrelation function and establishes their asymptotic properties. The article then illustrates the use of these new estimators on both simulated and real time series. The examples clearly demonstrate the strong practical benefits of local estimators for time series that exhibit nonstationarities
Plasma REST: a novel candidate biomarker of Alzheimer's disease is modified by psychological intervention in an at-risk population.
The repressor element 1-silencing transcription (REST) factor is a key regulator of the aging brain's stress response. It is reduced in conditions of stress and Alzheimer's disease (AD), which suggests that increasing REST may be neuroprotective. REST can be measured peripherally in blood plasma. Our study aimed to (1) examine plasma REST levels in relation to clinical and biological markers of neurodegeneration and (2) alter plasma REST levels through a stress-reduction intervention-mindfulness training. In study 1, REST levels were compared across the following four well-characterized groups: healthy elderly (n=65), mild cognitive impairment who remained stable (stable MCI, n=36), MCI who later converted to dementia (converter MCI, n=29) and AD (n=65) from the AddNeuroMed cohort. REST levels declined with increasing severity of risk and impairment (healthy elderly>stable MCI>converter MCI>AD, F=6.35, P<0.001). REST levels were also positively associated with magnetic resonance imaging-based hippocampal and entorhinal atrophy and other putative blood-based biomarkers of AD (Ps<0.05). In study 2, REST was measured in 81 older adults with psychiatric risk factors for AD before and after a mindfulness-based stress reduction intervention or an education-based placebo intervention. Mindfulness-based training caused an increase in REST compared with the placebo intervention (F=8.57, P=0.006), and increased REST was associated with a reduction in psychiatric symptoms associated with stress and AD risk (Ps<0.02). Our data confirm plasma REST associations with clinical severity and neurodegeneration, and originally, that REST is modifiable by a psychological intervention with clinical benefit
Change-Point Analysis of Asset Price Bubbles with Power-Law Hazard Function
We present a methodology to identify change-points in financial markets where the governing regime shifts from a constant rate-of-return, i.e. normal growth, to superexponential growth described by a power-law hazard rate. The latter regime corresponds, in our view, to financial bubbles driven by herding behaviour of market participants. Assuming that the time series of log-price returns of a financial index can be modelled by arithmetic Brownian motion, with an additional jump process with power-law hazard function to approximate the superexponential growth, we derive a threshold value of the hazard-function control parameter, allowing us to decide in which regime the market is more likely to be at any given time. An analysis of the Standard \& Poors 500 index over the last 60 years provides evidence that the methodology has merit in identifying when a period of herding behaviour begins, and, perhaps more importantly, when it ends
Plasma REST: A novel candidate biomarker of Alzheimer\u27s disease is modified by psychological intervention in an at-risk population
The repressor element 1-silencing transcription (REST) factor is a key regulator of the aging brain’s stress response. It is reduced in conditions of stress and Alzheimer’s disease (AD), which suggests that increasing REST may be neuroprotective. REST can be measured peripherally in blood plasma. Our study aimed to (1) examine plasma REST levels in relation to clinical and biological markers of neurodegeneration and (2) alter plasma REST levels through a stress-reduction intervention—mindfulness training. In study 1, REST levels were compared across the following four well-characterized groups: healthy elderly (n=65), mild cognitive impairment who remained stable (stable MCI, n=36), MCI who later converted to dementia (converter MCI, n=29) and AD (n=65) from the AddNeuroMed cohort. REST levels declined with increasing severity of risk and impairment (healthy elderly>stable MCI>converter MCI>AD, F=6.35, P<0.001). REST levels were also positively associated with magnetic resonance imaging-based hippocampal and entorhinal atrophy and other putative blood-based biomarkers of AD (Ps<0.05). In study 2, REST was measured in 81 older adults with psychiatric risk factors for AD before and after a mindfulness-based stress reduction intervention or an education-based placebo intervention. Mindfulness-based training caused an increase in REST compared with the placebo intervention (F=8.57, P=0.006), and increased REST was associated with a reduction in psychiatric symptoms associated with stress and AD risk (Ps<0.02). Our data confirm plasma REST associations with clinical severity and neurodegeneration, and originally, that REST is modifiable by a psychological intervention with clinical benefit
Summary report on excavations at Tell Khaiber, an administrative centre of the Sealand period, 2013-2017
Excavations at Tell Khaiber by the Ur Region Archaeological Project have revealed a substantial building (hereafter the Public Building) dating to the mid-second millennium BC. The results are significant for several reasons: they shed light on Babylonian provincial administration; they reveal a previously unknown type of fortified monumental building; and they produced a provenanced, dated archive of the little-understood Sealand Dynasty. Here we give a summary of the main results, including the architecture and the material culture. There are also comments on the historical background, and a discussion of the form and function of the Public Building
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