19,657 research outputs found
Modelling mortality rates using GEE models
Generalised estimating equation (GEE) models are extensions of generalised
linear models by relaxing the assumption of independence. These models are appropriate
to analyze correlated longitudinal responses which follow any distribution that is a member
of the exponential family. This model is used to relate daily mortality rate of Maltese
adults aged 65 years and over with a number of predictors, including apparent temperature,
season and year. To accommodate the right skewed mortality rate distribution a Gamma
distribution is assumed. An identity link function is used for ease of interpretating the
parameter estimates. An autoregressive correlation structure of order 1 is used since
correlations decrease as distance between observations increases. The study shows that
mortality rate and temperature are related by a quadratic function. Moreover, the GEE
model identifies a number of significant main and interaction effects which shed light on
the effect of weather predictors on daily mortality rates.peer-reviewe
Stochastic modeling of Congress
We analyze the dynamics of growth of the number of congressmen supporting the
resolution HR1207 to audit the Federal Reserve. The plot of the total number of
co-sponsors as a function of time is of "Devil's staircase" type. The
distribution of the numbers of new co-sponsors joining during a particular day
(step height) follows a power law. The distribution of the length of intervals
between additions of new co-sponsors (step length) also follows a power law. We
use a modification of Bak-Tang-Wiesenfeld sandpile model to simulate the
dynamics of Congress and obtain a good agreement with the data
Stochastic modeling of soil salinity
A minimalist stochastic model of primary soil salinity is proposed, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The long term probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equation to a single stochastic differential equation driven by multiplicative Poisson noise. The novel analytical solutions provide insight on the interplay of the main soil, plant and climate parameters responsible for long-term soil salinization. In particular, they show the existence of two distinct regimes, one where the mean salt mass remains nearly constant (or decreases) with increasing rainfall frequency, and another where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in long-term soil salinization trends, with significant consequences e.g. for climate change impacts on rain-fed agricultur
Stochastic Modeling of Hybrid Cache Systems
In recent years, there is an increasing demand of big memory systems so to
perform large scale data analytics. Since DRAM memories are expensive, some
researchers are suggesting to use other memory systems such as non-volatile
memory (NVM) technology to build large-memory computing systems. However,
whether the NVM technology can be a viable alternative (either economically and
technically) to DRAM remains an open question. To answer this question, it is
important to consider how to design a memory system from a "system
perspective", that is, incorporating different performance characteristics and
price ratios from hybrid memory devices.
This paper presents an analytical model of a "hybrid page cache system" so to
understand the diverse design space and performance impact of a hybrid cache
system. We consider (1) various architectural choices, (2) design strategies,
and (3) configuration of different memory devices. Using this model, we provide
guidelines on how to design hybrid page cache to reach a good trade-off between
high system throughput (in I/O per sec or IOPS) and fast cache reactivity which
is defined by the time to fill the cache. We also show how one can configure
the DRAM capacity and NVM capacity under a fixed budget. We pick PCM as an
example for NVM and conduct numerical analysis. Our analysis indicates that
incorporating PCM in a page cache system significantly improves the system
performance, and it also shows larger benefit to allocate more PCM in page
cache in some cases. Besides, for the common setting of performance-price ratio
of PCM, "flat architecture" offers as a better choice, but "layered
architecture" outperforms if PCM write performance can be significantly
improved in the future.Comment: 14 pages; mascots 201
Stochastic modeling for the COMET-assay
We present a stochastic model for single cell gel electrophoresis (COMET-assay) data. Essential is the use of point process structures, renewal theory and reduction to intensity histograms for further data analysis
Stochastic modeling of a serial killer
We analyze the time pattern of the activity of a serial killer, who during
twelve years had murdered 53 people. The plot of the cumulative number of
murders as a function of time is of "Devil's staircase" type. The distribution
of the intervals between murders (step length) follows a power law with the
exponent of 1.4. We propose a model according to which the serial killer
commits murders when neuronal excitation in his brain exceeds certain
threshold. We model this neural activity as a branching process, which in turn
is approximated by a random walk. As the distribution of the random walk return
times is a power law with the exponent 1.5, the distribution of the
inter-murder intervals is thus explained. We illustrate analytical results by
numerical simulation. Time pattern activity data from two other serial killers
further substantiate our analysis
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