A novel nonlinear least squares frequency estimation method which uses only a one-dimensional search routine has been recently proposed in [1]. In this paper, the variance of the estimator is analyzed at high signal-tonoise ratios. An analytical expression for the variance is derived. The dependence of the variance on the signal-tonoise ratio, the number of data partitions, the length of each p...

Research examining the formative specification of constructs has highlighted the need for researchers to capture all relevant causes of a construct of interest. However, the consequences of omitting a formative indicator have not been thoroughly examined. Given that one of the commonly employed techniques for modeling formatively specified constructs, Partial Least Squares, implicitly assumes t...

This paper considers the IV estimation of spatial autoregressive models with endogenous regressors in the presence of many instruments. To improve asymptotic e¢ ciency, it may be desirable to use many valid instruments. However, …nite sample properties of IV estimators can be sensitive to the number of instruments. For a spatial model with endogenous regressors, this paper derives the asymptoti...

If globally high dimensional data has locally only low dimensional distributions, it is advantageous to perform a local dimensionality reduction before further processing the data. In this paper we examine several techniques for local dimensionality reduction in the context of locally weighted linear regression. As possible candidates, we derive local versions of factor analysis regression, pri...

Abstract In August 2020 we published “Comprehensive Internal Model Data for Three Portfolios” as an outcome of our work the committee “Actuarial Science” German Actuarial Association. The data sets include realistic cash-flow models outputs used proxy modelling life and health insurers. Using these data, implement hitherto most promising model in modeling consisting ensembles feed-forward neura...

Partial Least Squares (PLS) has become an increasingly popular approach to testing research models with multiple proposed causality links. Moreover, recent interest in the specification of constructs in a formative manner has accentuated this tendency, given the purported ability of PLS to handle this methodological development. While a review of the literature reveals an extensive use of PLS i...

In this paper we consider the problem of determining the number of structural changes in multiple linear regression models via group fused Lasso (least absolute shrinkage and selection operator). We show that with probability tending to one our method can correctly determine the unknown number of breaks and the estimated break dates are sufficiently close to the true break dates. We obtain esti...

Incomplete paired comparison is an important scaling technique in vision science since the total number of paired comparisons for n stimuli is n(n-1)/2 which becomes prohibitive for large values of n. However, the experimental designer often struggles with questions such as what is the smallest limit for the proportion of paired comparisons included that will still allow reliable estimations of...

This paper presents a stochastic analysis of the Filtered-X LMS algorithm. The mean weight vector recursion is derived for slow adaptation and for a white reference signal without use of independence theory. The Wiener solution is determined explicitly as a function of the input statistics and the impulse responses of the primary and secondary signal paths. It is shown that the steady-state mea...