Estimating factor models for multivariate volatilities : an innovation expansion method

We introduce an innovation expansion method for estimation of factor models for conditional variance (volatility) of a multivariate time series. We estimate the factor loading space and the number of factors by a stepwise optimization algorithm on expanding the "white noise space". Simulation and a real data example are given for illustration

The adequacy of life insurance: evidence from the health and retirement survey

This study examines life insurance adequacy among married American couples approaching retirement based on the 1992 Health and Retirement Survey with matched Social Security earnings histories. It evaluates each household's life insurance needs based on new financial planning software that embodies a life-cycle-planning model and covers a broad array of demographic, economic, and financial characteristics. A sizable minority of households are significantly underinsured. Almost one third of wives and over 10 percent of husbands would have suffered living-standard reductions greater than 20 percent had their spouses died in 1992.Insurance ; Life insurance companies

How much should Americans be saving for retirement?

How much should Americans save prior to retirement? Given Social Security's shaky financial condition, this is a critical question for baby boomers. A financial planning program-ESPlanner-is applied to data from the Health and Retirement Survey (HRS) to consider the amount that households approaching retirement should save.Retirement ; Saving and investment ; Social security

IgM-producing tumors in the BALB/c mouse: a model for B-cell maturation

Five adjuvant induced BALB/c tumors producing IgM—McPc 1748, W 3469, TEPC 183, McPc 774, and Y 5781—were characterized morphologically by electron microscopy, analysis of the distribution of surface-bound and intracytoplasmic IgM using immunofluorescence, and by biochemical study of IgM synthesis, turnover, and secretion. The cells of different tumors appear to represent different stages in B-cell maturation when compared to normal, lipopolysaccharide-stimulated B cells. Thus, McPc 1748 tumor cells resemble 10–25-h stimulated normal B cells, 3469 cells resemble 20–35-h stimulated B cells, TEPC 183 cells resemble 45–65-h stimulated B cells, Y 5781 cells resemble 80–110-h stimulated B cells, and McPc 774 cells resemble 100–130-h stimulated B cells

On the detectability of non-trivial topologies

We explore the main physical processes which potentially affect the topological signal in the Cosmic Microwave Background (CMB) for a range of toroidal universes. We consider specifically reionisation, the integrated Sachs-Wolfe (ISW) effect, the size of the causal horizon, topological defects and primordial gravitational waves. We use three estimators: the information content, the S/N statistic and the Bayesian evidence. While reionisation has nearly no effect on the estimators, we show that taking into account the ISW strongly decreases our ability to detect the topological signal. We also study the impact of varying the relevant cosmological parameters within the 2 sigma ranges allowed by present data. We find that only Omega_Lambda, which influences both ISW and the size of the causal horizon, significantly alters the detection for all three estimators considered here.Comment: 11 pages, 9 figure

SZ and CMB reconstruction using Generalized Morphological Component Analysis

In the last decade, the study of cosmic microwave background (CMB) data has become one of the most powerful tools to study and understand the Universe. More precisely, measuring the CMB power spectrum leads to the estimation of most cosmological parameters. Nevertheless, accessing such precious physical information requires extracting several different astrophysical components from the data. Recovering those astrophysical sources (CMB, Sunyaev-Zel'dovich clusters, galactic dust) thus amounts to a component separation problem which has already led to an intense activity in the field of CMB studies. In this paper, we introduce a new sparsity-based component separation method coined Generalized Morphological Component Analysis (GMCA). The GMCA approach is formulated in a Bayesian maximum a posteriori (MAP) framework. Numerical results show that this new source recovery technique performs well compared to state-of-the-art component separation methods already applied to CMB data.Comment: 11 pages - Statistical Methodology - Special Issue on Astrostatistics - in pres

Supramolecular hierarchy among halogen and hydrogen bond donors in light-induced surface patterning

Halogen bonding, a noncovalent interaction possessing several unique features compared to the more familiar hydrogen bonding, is emerging as a powerful tool in functional materials design. Herein, we unambiguously show that one of these characteristic features, namely high directionality, renders halogen bonding the interaction of choice when developing azobenzene-containing supramolecular polymers for light-induced surface patterning. The study is conducted by using an extensive library of azobenzene molecules that differ only in terms of the bond-donor unit. We introduce a new tetrafluorophenol-containing azobenzene photoswitch capable of forming strong hydrogen bonds, and show that an iodoethynyl-containing azobenzene comes out on top of the supramolecular hierarchy to provide unprecedented photoinduced surface patterning efficiency. Specifically, the iodoethynyl motif seems highly promising in future development of polymeric optical and photoactive materials driven by halogen bonding