13,781 research outputs found
mgm: Estimating Time-Varying Mixed Graphical Models in High-Dimensional Data
We present the R-package mgm for the estimation of k-order Mixed Graphical
Models (MGMs) and mixed Vector Autoregressive (mVAR) models in high-dimensional
data. These are a useful extensions of graphical models for only one variable
type, since data sets consisting of mixed types of variables (continuous,
count, categorical) are ubiquitous. In addition, we allow to relax the
stationarity assumption of both models by introducing time-varying versions
MGMs and mVAR models based on a kernel weighting approach. Time-varying models
offer a rich description of temporally evolving systems and allow to identify
external influences on the model structure such as the impact of interventions.
We provide the background of all implemented methods and provide fully
reproducible examples that illustrate how to use the package
A Tutorial on Estimating Time-Varying Vector Autoregressive Models
Time series of individual subjects have become a common data type in
psychological research. These data allow one to estimate models of
within-subject dynamics, and thereby avoid the notorious problem of making
within-subjects inferences from between-subjects data, and naturally address
heterogeneity between subjects. A popular model for these data is the Vector
Autoregressive (VAR) model, in which each variable is predicted as a linear
function of all variables at previous time points. A key assumption of this
model is that its parameters are constant (or stationary) across time. However,
in many areas of psychological research time-varying parameters are plausible
or even the subject of study. In this tutorial paper, we introduce methods to
estimate time-varying VAR models based on splines and kernel-smoothing
with/without regularization. We use simulations to evaluate the relative
performance of all methods in scenarios typical in applied research, and
discuss their strengths and weaknesses. Finally, we provide a step-by-step
tutorial showing how to apply the discussed methods to an openly available time
series of mood-related measurements
Effects of the Nitric Oxide Synthease Inhibitor NG-nitro-L-arginine on the Erectile Response to Cavernous Nerve Stimulation in the Rabbit
Using baseline-dependent window functions for data compression and field-of-interest shaping in radio interferometry
In radio interferometry, observed visibilities are intrinsically sampled at
some interval in time and frequency. Modern interferometers are capable of
producing data at very high time and frequency resolution; practical limits on
storage and computation costs require that some form of data compression be
imposed. The traditional form of compression is a simple averaging of the
visibilities over coarser time and frequency bins. This has an undesired side
effect: the resulting averaged visibilities "decorrelate", and do so
differently depending on the baseline length and averaging interval. This
translates into a non-trivial signature in the image domain known as
"smearing", which manifests itself as an attenuation in amplitude towards
off-centre sources. With the increasing fields of view and/or longer baselines
employed in modern and future instruments, the trade-off between data rate and
smearing becomes increasingly unfavourable. In this work we investigate
alternative approaches to low-loss data compression. We show that averaging of
the visibility data can be treated as a form of convolution by a boxcar-like
window function, and that by employing alternative baseline-dependent window
functions a more optimal interferometer smearing response may be induced. In
particular, we show improved amplitude response over a chosen field of
interest, and better attenuation of sources outside the field of interest. The
main cost of this technique is a reduction in nominal sensitivity; we
investigate the smearing vs. sensitivity trade-off, and show that in certain
regimes a favourable compromise can be achieved. We show the application of
this technique to simulated data from the Karl G. Jansky Very Large Array (VLA)
and the European Very-long-baseline interferometry Network (EVN)
Travelling to exotic places with cavity QED systems
Recent theoretical schemes for utilizing cavity QED models as quantum
simulators are reviewed. By considering a quadrature representation for the
fields, it is shown how Jahn-Teller models, effective Abelian or non-Abelian
gauge potentials, transverse Hall currents, and relativistic effects naturally
arise in these systems. Some of the analytical predictions are verified
numerically using realistic experimental parameters taking into account for
system losses. Thereby demonstrating their feasibility with current
experimental setups.Comment: 5 pages, 3 figure
Asset pricing lessons for modeling business cycles.
We develop a model which accounts for the observed equity premium and average risk free rate, without implying counterfactually high risk aversion. The model also does well in aceounting for business cycle phenomena. With respect to the conventional measures of business cycle volatility and comovement with output, the model does roughly as well as the standard business cycle model. On two other dimensions, the model's business cycle implications are actually improved. Its enhanced internal propagation allows it to account for the fact that there is positive persistenee in output growth, and the model also provides a resolution to the "excess sensitivity puzzle" for consumption and income. Key features of the model are habit persistence preferences, and a multisector technology with limited intersectoral mobility of factors of production.
Issues Relevant to C-H Activation at Platinum(II): Comparative Studies between Cationic, Zwitterionic, and Neutral Platinum(II) Compounds in Benzene Solution
Cationic late metal systems are being highly scrutinized due to
their propensity to mediate so-called electrophilic C-H
activation reactions. This contribution compares the reactivity
of highly reactive cationic platinum(II) systems with
structurally related but neutral species. Our experimental
design exploits isostructural neutral and cationic complexes
supported by bis(phosphine) ligands amenable to mechanistic
examination in benzene solution. The data presented herein
collectively suggests that neutral platinum complexes can be
equally if not more reactive towards benzene than their
cationic counter-parts. Moreover, a number of unexpected
mechanistic distinctions between the two systems arise that
help to explain their respective reactivity
The angular power spectrum of radio emission at 2.3 GHz
We have analysed the Rhodes/HartRAO survey at 2326 MHz and derived the global
angular power spectrum of Galactic continuum emission. In order to measure the
angular power spectrum of the diffuse component, point sources were removed
from the map by median filtering. A least-square fit to the angular power
spectrum of the entire survey with a power law spectrum C_l proportional to
l^{-alpha}, gives alpha = 2.43 +/- 0.01 for l = 2-100. The angular power
spectrum of radio emission appears to steepen at high Galactic latitudes and
for observed regions with |b| > 20 deg, the fitted spectral index is alpha =
2.92 +/- 0.07. We have extrapolated this result to 30 GHz (the lowest frequency
channel of Planck) and estimate that no significant contribution to the sky
temperature fluctuation is likely to come from synchrotron at degree-angular
scalesComment: 10 pages, 10 figures, accepted for publication by Astronomy &
Astrophysic
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