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

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