Showing papers on "Matching (statistics) published in 1979"

Using Multivariate Matched Sampling and Regression Adjustment to Control Bias in Observational Studies

Abstract: Monte Carlo methods are used to study the efficacy of multivariate matched sampling and regression adjustment for controlling bias due to specific matching variables X when dependent variables are moderately nonlinear in X. The general conclusion is that nearest available Mahalanobis metric matching in combination with regression adjustment on matched pair differences is a highly effective plan for controlling bias due to X.

Two-level DP-matching--A dynamic programming-based pattern matching algorithm for connected word recognition

Abstract: This paper reports a pattern matching approach to connected word recognition. First, a general principle of connected word recognition is given based on pattern matching between unknown continuous speech and artificially synthesized connected reference patterns. Time-normalization capability is allowed by use of dynamic programming-based time-warping technique (DP-matching). Then, it is shown that the matching process is efficiently carried out by breaking it down into two steps. The derived algorithm is extensively subjected to recognition experiments. It is shown in a talker-adapted recognition experiment that digit data (one to four digits) connectedly spoken by five persons are recognized with as high as 99.6 percent accuracy. Computation time and memory requirement are both proved to be within reasonable limits.

Operant matching is not a logical consequence of maximizing reinforcement rate

Abstract: The distribution of behavior between concurrently available schedules of reinforcement approximates the distribution of reinforcements between the schedules. This equality, called matching, has been explained as an instance of the principle that organisms maximize reinforcement rate. However, a precise account of the relationship between the distribution of behavior and reinforcement rate on the standard concurrent schedule shows that matching and maximizing are different.

Experiments in relevance weighting of search terms

Abstract: Following successful initial tests of theoretically-based schemes for relevance weighting of search terms, further experiments were undertaken to validate these results. The experiments were designed to investigate weighting for a large document set, poor matching conditions, heterogeneous data, and limited relevance information, i.e. the use of weighting in more realistic conditions than the initial ones. The results confirm the earlier ones: very striking improvements in retrieval performance were obtained, especially for the theoretically best-founded weighting formula. The experiments illustrate a much more promising application of statistical methods to indexing and searching than any studied hitherto.

Matching algorithms.

Abstract: Given a graph G = (V, E), a matching M is a set of edges with the property that no two of the edges have an endpoint in common. We say that a vertex v ∈ V is matched if v is incident to an edge in the matching. Otherwise the vertex is unmatched. A matching is maximum if there is no matching of greater cardinality. In particular, a maximum matching is called perfect if every vertex of G is matched. A bipartite graph G is a graph in which the vertices of G can be partitioned in two sets A and B with the property that every edge in G has one endpoint in A and one in B. In the case of bipartite graphs, the following theorem characterizes graphs that have a perfect matching. For U ⊆ A denote N (U) the set of vertices that are adjacent to vertices in U. Theorem 1 (Hall). A bipartite graph with sets of vertices A, B has a perfect matching iff |A| = |B| and (∀U ⊆ A)|N (U)| ≥ |U |. Proof. If a bipartite graph has a perfect matching, then it is easy to see that the right hand side is a necessary condition. We will now prove the reverse implication. First note that the RHS condition implies So G has a matching M of A \ {u} into B \ {v}. Then M 1 = M ∪ {e} is a matching of A into B in G. 2. Now suppose the opposite to the previous case: there exists A ⊂ A nonempty such that |N (A)| = |A |. Let G 1 be the graph induced by A ∪ N (A). Let G 2 be the graph induced by G − A − N (A).

Matching models in the analysis of cross-classifications

Abstract: Inference models motivated by the combinatorial chance literature and the concept of object matching may be used in the analysis of a contingency table if the conditional assumption of fixed row and column totals is imposed. More specifically, by developing a matching reinterpretation for several problems of interest in the prediction analysis of cross-classifications—as defined by Hildebrand, Laing and Rosenthal, appropriate significance tests can be given that may differ from those justified by the more common multinomial models. In the course of the paper the distinction between a degree-1 statistic (based on the relationship between single objects) and a degree-2 statistic (based on the relationship between object pairs) is reviewed in some detail. Also, several specializations are presented to topics of current methodological importance in psychology; for instance, a number of references are made to the measurement of nominal scale response agreement between two raters.

A new statistical approach to the alignment of time series

Abstract: Summary. Much research in the Earth Sciences is centred on the search for similarities in waveforms or amongst sets of observations. For example, in seismology and palaeomagnetism, this matching of records is used to align several series of observations against one another or to compare one set of observations against a master series. This paper gives a general mathematical and statistical formulation of the problem of transforming, linearly or otherwise, the time-scale or depth-scale of one series of data relative to another. Existing approaches to this problem, involving visual matching or the use of correlation coefficients, are shown to have several serious deficiencies, and a new statistical procedure, using least-squares cubic splines, is presented. The new method provides not only a best estimate of the ‘stretching function’ defining the relative alignment of the two series of observations, but also a statement, by means of confidence regions, of the precision of this transformation. The new procedure is illustrated by analyses of artificially generated data and of palaeomagnetic observations from two cores from Lake Vuokonjarvi, Finland. It may be applied in a wide variety of situations, wherever the observations satisfy the general underlying mathematical model.

The Need for Autonomy Among Managers

Abstract: Some MBA candidates have a high need for autonomy and in some managerial positions the manager should have autonomy in order to get the job done. Approaches to exploring the concept of autonomy, its identification, and its potential for improving managerial matching, along with some evidence, are proposed.

Exact Model-Matching of 2-D Systems via State Feedback

Abstract: This paper considers the problem of matching the transfer function matrix of a given two-dimensional (2-D) system to that of a desired 2-D model using state feedback. The approach followed refers to systems having square transfer function matrices and reduces the problem to that of solving a linear system of equations. Furthermore, necessary and sufficient conditions are established for exact matching. An example is included to illustrate the proposed method.

Performance Comparison of Scene Matching Techniques

Abstract: The problem of matching two images of the same scene, taken by different sensors under different viewing geometries, is a challenging problem in the field of image processing and pattern recognition. The scenes are usually transformed so drastically by the different viewing geometries and sensor characteristics that it is extremely difficult, if not impossible, to match the original images without the proper data processing. Geometric and intensity transformations must be performed to bring the matching elements and their intensity into a one-to-one correspondence. Objects of interest represented by subimages of one scene were located in the other using scene matching techniques with intensity difference and edge features as measurement features. Performance characteristics of the matches by these techniques are presented in terms of the probability of a match as a function of the probability of false fix.

Principle of environmental energy matching for estimating potential economic value, a rebuttal

Abstract: (1979). Principle of environmental energy matching for estimating potential economic value, a rebuttal. Coastal Zone Management Journal: Vol. 5, No. 3, pp. 239-241.

Behavioral Choice and Social Reinforcement: Step Function Versus Matching

Abstract: This is a theoretical article designed to summarize and evaluate social research relevant to two models of behavioral choice, a maximizing step function and a matching equation. Research is reviewed for a range of social situations, and, in each case, the data are described by a matching equation, never a step function. Several implications of the matching equations are

The matching of rigid bodies; a program using Kabsch's procedure

Abstract: The program BMFIT, used to find the weighted best least-squares fit of two rigid bodies, has been modified to take advantage of a proposal by Kabsch in which iteration is avoided.

On matching principles

Abstract: Matching principles are the key of asymptotic analysis for singular perturbation problems. Starting with some classical definitions in asymptotics we recall the principal results which have been obtained to match asymptotic expansions of a singular function; these classical results are based on Kaplun's extension theorem. After Kaplun and Fraenkel, most of the results are from W. Eckhaus; in fact, he was the first to say clearly that matching is not actually a consequence of overlapping. Following all these ideas, we discuss some theorems and rules which involve matching and try to explore some new ideas with the help of simple examples and counter-examples.

Nonparametric Model Matching of Linear Time-Invariant Multivariable Systems

Abstract: This paper considers the problem of matching a system under control to a model using output feedback when both the given system and the model are described by nonparametric models, such as the impulse response matrix. Conditions are established for exact matching, the problem being reduced to that of solving a linear system of equations. The present paper constitutes the first results in non-parametric model matching which appear to be very suitable for practical applications.

Optimal selection of matched pairs from large data bases

Abstract: This paper considers the problem of selecting matched pairs of observations for the reduction of bias in statistical hypothesis testing. A Euclidean distance function is suggested for measuring the similarity between paired observations. The matching process is then formulated initially as an assignment problem. Alternative formulations of the problem that would reduce computational difficulty are considered.

Frequency matching device for wireless apparatus

Abstract: PURPOSE:To secure a simple and easy matching of both the transmitting and receiving frequencies to the level near the maximum receiving sensitivity, by lowering the sensitivity of the receiving antenna less than the normal level.

A model for studying some organizational effects of an increase in the size of R&D projects

Abstract: Increasing size of R&D projects poses problems of matching workload with capacity when the size of the R&D department and exploiting capability remain fixed. Potential diseconomies arising from such mismatching are described, and strategies for alleviating such diseconomies are discussed.