The finite-sample effects of VAR dimensions on OLS bias, OLS variance, and minimum MSE estimators: Purely nonstationary case

Vector autoregressions (VARs) are an important tool in time series analysis. However, relatively little is known about the nite-sample behaviour of parameter estimators. We address this issue, by investigating ordinary least squares (OLS) estimators given a data generating process that is a purely nonstationary rst-order VAR. Specically, we use Monte Carlo simulation and numerical optimization to derive response surfaces for OLS bias and variance, in terms of VAR dimensions, given correct and (several types of) over-parameterization of the model: we include a constant, and a constant and trend, and introduce excess lags. We then examine the correction factors required for the least squares estimator to attain minimum mean squared error (MSE). Our results improve and extend one of the main nite-sample analytical bias results of Abadir, Hadri and Tzavalis (Econometrica 67 (1999) 163), generalize the univariate variance and MSE ndings of Abadir (Econ. Lett. 47 (1995) 263), and complement various asymptotic studies

A comparison of in-sample forecasting methods

In-sample forecasting is a recent continuous modification of well-known forecasting methods based on aggregated data. These aggregated methods are known as age-cohort methods in demography, economics, epidemiology and sociology and as chain ladder in non-life insurance. Data is organized in a two-way table with age and cohort as indices, but without measures of exposure. It has recently been established that such structured forecasting methods based on aggregated data can be interpreted as structured histogram estimators. Continuous in-sample forecasting transfers these classical forecasting models into a modern statistical world including smoothing methodology that is more efficient than smoothing via histograms. All in-sample forecasting estimators are collected and their performance is compared via a finite sample simulation study. All methods are extended via multiplicative bias correction. Asymptotic theory is being developed for the histogram-type method of sieves and for the multiplicatively corrected estimators. The multiplicative bias corrected estimators improve all other known in-sample forecasters in the simulation study. The density projection approach seems to have the best performance with forecasting based on survival densities being the runner-up

Blazars in the Fermi Era: The OVRO 40-m Telescope Monitoring Program

The Large Area Telescope (LAT) aboard the Fermi Gamma-ray Space Telescope provides an unprecedented opportunity to study gamma-ray blazars. To capitalize on this opportunity, beginning in late 2007, about a year before the start of LAT science operations, we began a large-scale, fast-cadence 15 GHz radio monitoring program with the 40-m telescope at the Owens Valley Radio Observatory (OVRO). This program began with the 1158 northern (declination>-20 deg) sources from the Candidate Gamma-ray Blazar Survey (CGRaBS) and now encompasses over 1500 sources, each observed twice per week with a ~4 mJy (minimum) and 3% (typical) uncertainty. Here, we describe this monitoring program and our methods, and present radio light curves from the first two years (2008 and 2009). As a first application, we combine these data with a novel measure of light curve variability amplitude, the intrinsic modulation index, through a likelihood analysis to examine the variability properties of subpopulations of our sample. We demonstrate that, with high significance (7-sigma), gamma-ray-loud blazars detected by the LAT during its first 11 months of operation vary with about a factor of two greater amplitude than do the gamma-ray-quiet blazars in our sample. We also find a significant (3-sigma) difference between variability amplitude in BL Lacertae objects and flat-spectrum radio quasars (FSRQs), with the former exhibiting larger variability amplitudes. Finally, low-redshift (z<1) FSRQs are found to vary more strongly than high-redshift FSRQs, with 3-sigma significance. These findings represent an important step toward understanding why some blazars emit gamma-rays while others, with apparently similar properties, remain silent.Comment: 23 pages, 24 figures. Submitted to ApJ

Calibration and performance of the photon sensor response of FACT -- The First G-APD Cherenkov telescope

The First G-APD Cherenkov Telescope (FACT) is the first in-operation test of the performance of silicon photo detectors in Cherenkov Astronomy. For more than two years it is operated on La Palma, Canary Islands (Spain), for the purpose of long-term monitoring of astrophysical sources. For this, the performance of the photo detectors is crucial and therefore has been studied in great detail. Special care has been taken for their temperature and voltage dependence implementing a correction method to keep their properties stable. Several measurements have been carried out to monitor the performance. The measurements and their results are shown, demonstrating the stability of the gain below the percent level. The resulting stability of the whole system is discussed, nicely demonstrating that silicon photo detectors are perfectly suited for the usage in Cherenkov telescopes, especially for long-term monitoring purpose

A simple method to identify significant effects in unreplicated two-level factorial designs

This article proposes a generalization and improvement on the method of Lenth (1989). The problem is solved by fixing outliers in highly contaminated samples. To do this a scale robust estimator is obtained and its performance is analyzed using computer simulations. The method is extremely simple to use and leads to the same results as the more complex one proposed by Box and Meyer (1986)

The matter distribution in the local Universe as derived from galaxy groups in SDSS DR12 and 2MRS

Context. Friends-of-friends algorithms are a common tool to detect galaxy groups and clusters in large survey data. In order to be as precise as possible, they have to be carefully calibrated using mock catalogues. Aims. We create an accurate and robust description of the matter distribution in the local Universe using the most up-to-date available data. This will provide the input for a specific cosmological test planned as follow-up to this work, and will be useful for general extragalactic and cosmological research. Methods. We created a set of galaxy group catalogues based on the 2MRS and SDSS DR12 galaxy samples using a friends-of-friends based group finder algorithm. The algorithm was carefully calibrated and optimised on a new set of wide-angle mock catalogues from the Millennium simulation, in order to provide accurate total mass estimates of the galaxy groups taking into account the relevant observational biases in 2MRS and SDSS. Results. We provide four different catalogues (i) a 2MRS based group catalogue; (ii) an SDSS DR12 based group catalogue reaching out to a redshift z = 0.11 with stellar mass estimates for 70% of the galaxies; (iii) a catalogue providing additional fundamental plane distances for all groups of the SDSS catalogue that host elliptical galaxies; (iv) a catalogue of the mass distribution in the local Universe based on a combination of our 2MRS and SDSS catalogues. Conclusions. While motivated by a specific cosmological test, three of the four catalogues that we produced are well suited to act as reference databases for a variety of extragalactic and cosmological science cases. Our catalogue of fundamental plane distances for SDSS groups provides further added value to this paper.Comment: 31 pages, 25 figures, accepted for publication in A&

Robust online scale estimation in time series: A regression-free approach.

This paper presents variance extraction procedures for univariate time series. The volatility of a times series is monitored allowing for non-linearities, jumps and outliers in the level. The volatility is measured using the height of triangles formed by consecutive observations of the time series. This idea was proposed by Rousseeuw and Hubert (1996, Regression-free and robust estimation of scale for bivariate data, Computational Statistics and Data Analysis, 21, 67{85) in the bivariate setting. This paper extends their procedure to apply for online scale estimation in time series analysis. The statistical properties of the new methods are derived and nite sample properties are given. A nancial and a medical application illustrate the use of the procedures.Breakdown point; Inuence function; Online monitoring; Outliers; Robust scale estimation;