We discuss parameter estimation for discretely observed, ergodic diffusion processes where the diffusion coefficient does not depend on the parameter. We propose using an approximation of the continuous-time score function as an estimating function. The estimating function can be expressed in simple terms through the drift and the diffusion coefficient and is thus easy to calculate. Simulation ...

Robust estimators of a correlation coefficient based on: (i) direct robust counterparts of the sample correlation coefficient, (ii) nonparametric measures of correlation, (iii) robust regression, (iv) robust estimation of the variances of principal variables, (v) stable parameter estimation, and (vi) the preliminary rejection of outliers from the data with the subsequent application of the samp...

The maximal information coefficient (MIC) is a tool for finding the strongest pairwise relationships in a data set with many variables [1]. MIC is useful because it gives similar scores to equally noisy relationships of different types. This property, called equitability, is important for analyzing high-dimensional data sets. Here we formalize the theory behind both equitability and MIC in the ...

We present a high-frequency based method for analyzing a one-period futures hedging problem. The realized hedge ratio is constructed by applying the realized regression with the R-squared coefficient as an ex-post performance measure. The asymptotic theory enables us to assess the parameter estimation risk of the hedge ratios. An empirical study is conducted on the S&P 500 index and their hedgi...

We present fixed domain asymptotic results that establish consistent estimates of the variance and scale parameters for a Gaussian random field with a geometric anisotropic Matérn autocovariance in dimension d > 4. When d < 4 this is impossible due to the mutual absolute continuity of Matérn Gaussian random fields with different scale and variance (see Zhang [33]). Informally, when d > 4, we sh...

We discuss parameter estimation for discretely observed, ergodic diffusion processes where the diffusion coefficient does not depend on the parameter. We propose using an approximation of the continuous-time score function as an estimating function. The estimating function can be expressed in simple terms through the drift and the diffusion coefficient and is thus easy to calculate. Simulation ...

BACKGROUND In this paper we propose the use of the within-subject coefficient of variation as an index of a measurement's reliability. For continuous variables and based on its maximum likelihood estimation we derive a variance-stabilizing transformation and discuss confidence interval construction within the framework of a one-way random effects model. We investigate sample size requirements f...

Abstract Semivarying coefficient models are frequently used in statistical models. In this paper, under the condition that the coefficient functions possess different degrees of smoothness, a two-step method is proposed. In the case, one-step method for the smoother coefficient functions cannot be optimal. This drawback can be repaired by using the two-step estimation procedure. The asymptotic ...