Iterative tuning of the parameters of a restricted-order controller using the data acquired in closed-loop operation seems to be a promising idea, especially for tuning PID controllers in industrial applications. In this paper, a new tuning approach based on decorrelation is proposed. The basic idea is to make the output error between the designed and achieved closed-loop systems uncorrelated w...

Understanding the role of health information in food and nutrient demand has become an important issue over the last decade. Endogeneity and measurement error are two empirical problems that are inherent in this type of analysis. While some type of instrumental variables estimation would appear the obvious solution, this paper provides several theoretical and empirical reasons why this is not t...

Instrumental-variable (IV) methods were invented over 70 years ago, but remain uncommon in epidemiology. Over the past decade or so, non-parametric versions of IV methods have appeared that connect IV methods to causal and measurement-error models important in epidemiological applications. This paper provides an introduction to those developments, illustrated by an application of IV methods to ...

Instrumental variables (IVs) are used to control for confounding and measurement error in observational studies. They allow for the possibility of making causal inferences with observational data. Like propensity scores, IVs can adjust for both observed and unobserved confounding effects. Other methods of adjusting for confounding effects, which include stratification, matching and multiple reg...

This paper considers the nonparametric regression model with an additive error that is dependent on the explanatory variables. As is common in empirical studies in epidemiology and economics, it also supposes that valid instrumental variables are observed. A classical example in microeconomics considers the consumer demand function as a function of the price of goods and the income, both variab...

This paper reviews the main aspects involved with the management of instrumental errors associated with video-based optoelectronic stereophotogrammetry. Insights on how such errors propagate to kinematic quantities are of great interest in the field of human movement analysis to improve the precision and reliability of measurements. The review focuses on the technical assessment and analytical ...

Controllers in the linear parameter-varying (LPV) framework are commonly designed in continuoustime (CT) requiring accurate and low-order CT models of the system. However, identification of continuous-time LPV models is largely unsolved, representing a gap between the available LPV identification methods and the needs of control synthesis. In order to bridge this gap, direct identification of C...

The method of Instrumental Variables is suggested as an alternative to traditional methods for estimating the reliability of mental test scores which avoids certain drawbacks of these methods. The consistency and efficiency of the instrumental variable method are examined empirically using data from the British National Child Development Study in an analysis of 16 year, 11 year and 7 year old s...

This paper describes a method which simulates the timbre of the human voice through the orchestration of instrumental ensembles for classical music. The spectral envelope of speech is used as a model for the orchestration. The idea of this method is to synthesise the spectral envelope of a phoneme using the spectral envelopes of different sounds of music instruments. Large instrumental database...

For many years, various methods for the identification and estimation of parameters in linear, discrete-time transfer functions have been available and implemented in widely available Toolboxes for Matlab. This paper considers a unified Refined Instrumental Variable (RIV) approach to the estimation of discrete and continuous-time transfer functions characterized by a unified operator that can b...