A signal processing technique is presented to improve the angular rate accuracy of Micro-Electro-Mechanical System (MEMS) gyroscope by combining numerous gyroscopes. Based on the conditional correlation between gyroscopes, a dynamic data fusion model is established. Firstly, the gyroscope error model is built through Generalized Autoregressive Conditional Heteroskedasticity (GARCH) process to i...

The aim of this article is to investigate the dynamic correlation between the Global Economic Policy Uncertainty index (GEPU) and Non-Performing Loans (NPL) in Iran. The relationship between economic uncertainty and banking performance indices is significant because of the systemic importance of banks in every economy. We evaluated this relationship in this developing country, especially under ...

ABSTRACT. In paired randomized experiments units are grouped in pairs, often based on covariate information, with random assignment within the pairs. Average treatment effects are then estimated by averaging the within-pair differences in outcomes. Typically the variance of the average treatment effect estimator is estimated using the sample variance of the within-pair differences. However, con...

Conditional cumulants form a set of unique statistics which represent a sensible compromise between N -point correlation functions and cumulants measured from moments of counts in cells. They share accurate edge corrected estimators with N -point correlation functions, yet, they are as straightforward to measure and interpret as counts in cells. The conditional cumulants have three equivalent v...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

We model the conditional mean and volatility of stock returns as a latent vector autoregressive (VAR) process to study the contemporaneous and intertemporal relationship between expected returns and risk in a flexible statistical framework and without relying on exogenous predictors. We find a strong and robust negative correlation between the innovations to the conditional moments that leads t...

This paper considers tests and con…dence sets (CS’s) concerning the coe¢ cient on the endogenous variable in the linear IV regression model with homoskedastic normal errors and one right-hand side endogenous variable. The paper derives a …nite-sample lower bound function for the probability that a CS constructed using a two-sided invariant similar test has in…nite length and shows numerically t...

I introduce a conditional measure of skill, the correlation between fund's trades and future news of the stocks traded. Using this measure, I show that the average fund manager in the cross-section of U.S. equity mutual funds has stock picking skill. This skill is mainly driven by manager's ability to predict rm's cashow news. Importantly, this skill has short term persistence, which is not exp...

This study analyzed meteorological, clinical and economic factors in terms of their effects on monthly ED revenue and visitor volume. Monthly data from January 1, 2005 to September 30, 2009 were analyzed. Spearman correlation and cross-correlation analyses were performed to identify the correlation between each independent variable, ED revenue, and visitor volume. Autoregressive integrated movi...