Property Owning and Democracy-Do the Twain Ever Meet?

Starting from the Conservative assertion that home ownership fosters politically active and virtuous citizens, this paper examines two lines of argument in housing theory; (a) Jim Kemeny's thesis that owner occupation is closely linked to increasing privatism, i.e. a growth in lifestyles centred around the home and privacy rather than the workplace or the public affairs in a society, and (b) Peter Saunders' thesis that home owners will organise and mobilise politically in defence of their property interests if and when various government agencies threaten to remove their tax subsidies. To test these propositions empirically, data on the effects of the rapid and comprehensive dismantling of tax privileges to Swedish home owners in the 1980s and early 1990s are confronted with data on political interest, participation and knowledge as well as civic trust and responsibility from the Swedish election surveys of 1979, 1985 and 1991. Contrary to Conservative beliefs, home owners do not stand out as 'democratic examples'; with the exception of political knowledge and party membership, they are no more 'civil' or 'democratic' than other citizens. There is also not much to support Kemeny's 'privatism' or Saunders' 'reaction-to-threat' theses. Although home owners in Sweden saw their tax privileges diminishing rapidly during the 1980s and early 1990s, they do not show the distinctive patterns of change in democratic orientation and spirit predicted by these two housing theorists. To allow for an even more conclusive test of Kemeny's 'privatism' thesis, however, one must overcome the mismatch of income definitions in housing statistics and election survey data.     

Remarks on the mean square tracking error

The purpose of this paper is to extend recent results of Ljung and Priouret to a more general class of regressors.     

Psychometric considerations in the dimensional analysis of subjective picture quality

A discussion of the factors involved in the subjective perception of television picture quality is presented. Much of the work in this field is cited, and it is concluded that future work needs to consider a broader range of variables than has been looked at so far.     

Existence of discrete-time LQG-controllers

Existence results for the LQG-controller are investigated. An infimal Riccati equation based controller may potentially give closed loop eigenvalues on the unit circle. Assuming left and right invertibility it is shown that there exists an optimal controller if and only if the Riccati equation based controller stabilizes the closed loop system after removal of all its unobservable and uncontrollable modes. Furthermore this reduced controller is the optimal controller, and its transfer function is unique. This existence condition is a considerable simplification of the more general geometric condition recently derived by Trentelman and Stoorvogel.     

Performance analysis of general tracking algorithms

A general family of tracking algorithms for linear regression models is studied. It includes the familiar least mean square gradient approach, recursive least squares, and Kalman filter based estimators. The exact expressions for the quality of the obtained estimates are complicated. Approximate, and easy-to-use, expressions for the covariance matrix of the parameter tracking error are developed. These are applicable over the whole time interval, including the transient, and the approximation error can be explicitly calculated     

Nonlinear black-box modeling in system identification: a unified overview

A nonlinear black-box structure for a dynamical system is a model structure that is prepared to describe virtually any nonlinear dynamics. There has been considerable recent interest in this area, with structures based on neural networks, radial basis networks, wavelet networks and hinging hyperplanes, as well as wavelet-transform-based methods and models based on fuzzy sets and fuzzy rules. This paper describes all these approaches in a common framework, from a user's perspective. It focuses on what are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques. It is pointed out that the nonlinear structures can be seen as a concatenation of a mapping form observed data to a regression vector and a nonlinear mapping from the regressor space to the output space. These mappings are discussed separately. The latter mapping is usually formed as a basis function expansion. The basis functions are typically formed from one simple scalar function, which is modified in terms of scale and location. The expansion from the scalar argument to the regressor space is achieved by a radial- or a ridge-type approach. Basic techniques for estimating the parameters in the structures are criterion minimization, as well as two-step procedures, where first the relevant basis functions are determined, using data, and then a linear least-squares step to determine the coordinates of the function approximation. A particular problem is to deal with the large number of potentially necessary parameters. This is handled by making the number of ‘used’ parameters considerably less than the number of ‘offered’ parameters, by regularization, shrinking, pruning or regressor selection.     

Renal sodium excretion after oral or intravenous sodium loading in sodium-deprived normotensive and spontaneously hypertensive rats

Spontaneously hypertensive rats (SHR) and normotensive Wistar-Kyoto (WKY) rats that had been on a low sodium diet for 3 days were given 1.5 mmol sodium chloride kg-1 body weight either orally or intravenously. The rats receiving an oral sodium load showed a greater natriuresis than those receiving the same saline load intravenously. No increase of renal sodium excretion was observed when the rats received a hypertonic mannitol solution orally. The cumulative sodium excretion during the 8 h following oral loading was two to three times larger in SHR than in WKY, whereas no difference between strains could be demonstrated after giving saline intravenously. Furthermore, after switching from normal to low sodium diet the rate of decrease of renal sodium excretion was greater in SHR than in WKY rats. It is proposed that there exists a gastrointestinal sensory mechanism for sodium controlling the renal sodium excretion. Furthermore, it is suggested that the function of this mechanism differs between SHR and WKY.     

Performance analysis of the forgetting factor RLS algorithm

An analysis is given of the performance of the standard forgetting factor recursive least squares (RLS) algorithm when used for tracking time-varying linear regression models. Three basic results are obtained: (1) the ‘P-matrix’ in the algorithm remains bounded if and only if the (time-varying) covariance matrix of the regressors is uniformly non-singular; (2) if so, the parameter tracking error covariance matrix is of the order O(μ + γ²/μ), where μ = 1 - λ, λ is the forgetting factor and γ is a quantity reflecting the speed of the parameter variations; (3) this covariance matrix can be arbitrarily well approximated (for small enough μ) by an expression that is easy to compute.     

Probabilistic heuristic estimates

Though they constitute the major knowledge source in problem-solving systems, no unified theory of heuristics has emerged. Pearl [15] defines heuristics as criteria, methods, or principles for deciding which among several alternative courses of action promises to be the most effective in order to achieve some goal. The absence of a more precise definition has impeded our efforts to understand, utilize, and discover heuristics. Another consequence is that problem-solving techniques which rely on heuristic knowledge cannot be relied upon to act rationally — in the sense of the normative theory of rationality.To provide a sound basis for BPS, the Bayesian Problem-Solver, we have developed a simple formal theory of heuristics, which is general enough to subsume traditional heuristic functions as well as other forms of problem-solving knowledge, and to straddle disparate problem domains. Probabilistic heuristic estimates represent a probabilistic association of sensations with prior experience — specifically, a mapping from observations directly to subjective probabilities which enables the use of theoretically principled mechanisms for coherent inference and decision making during problem-solving. This paper discusses some of the implications of this theory, and describes its successful application in BPS.This research was made possible by support from Heuristicrats, the National Aeronautics and Space Administration, and the Rand Corporation.