Robust regression applied to fractal/multifractal analysis.

Fractal and multifractal are concepts that have grown increasingly popular in recent years in the soil analysis, along with the development of fractal models. One of the common steps is to calculate the slope of a linear fit commonly using least squares method. This shouldn?t be a special problem, however, in many situations using experimental data the researcher has to select the range of scales at which is going to work neglecting the rest of points to achieve the best linearity that in this type of analysis is necessary. Robust regression is a form of regression analysis designed to circumvent some limitations of traditional parametric and non-parametric methods. In this method we don?t have to assume that the outlier point is simply an extreme observation drawn from the tail of a normal distribution not compromising the validity of the regression results. In this work we have evaluated the capacity of robust regression to select the points in the experimental data used trying to avoid subjective choices. Based on this analysis we have developed a new work methodology that implies two basic steps: ? Evaluation of the improvement of linear fitting when consecutive points are eliminated based on R pvalue. In this way we consider the implications of reducing the number of points. ? Evaluation of the significance of slope difference between fitting with the two extremes points and fitted with the available points. We compare the results applying this methodology and the common used least squares one. The data selected for these comparisons are coming from experimental soil roughness transect and simulated based on middle point displacement method adding tendencies and noise. The results are discussed indicating the advantages and disadvantages of each methodology.

Symposium on mathematics for engineering students being the proceedings of the joint sessions of the Chicago section of the American mathematical society and Section A, Mathematics, and Section D, Mechanical science and engineering of the American Association for the Advancement of Science held at the University of Chicago December 30 and 31, 1907.

Caption title: The American Association for the Advancement of Science. Section D--Mechanical science and engineering. Engineering Mathematics symposium.

Multiple classification analysis ; a report on a computer program for multiple regression using categorical predictors /

Bibliographical footnotes.

The use of lead compounds in pottery, from the potter's point of view.

Published "by request of the Joint Committee of the Allied Manufacturers' Associations of Great Britain."

Disentangling the impact of seroconversion age and set-point viral load on ART-free HIV survival

Thesis (Master's)--University of Washington, 2016-06

Effects of experimentally-induced anterior knee pain on knee joint position sense in healthy individuals

Purpose. The ability to sense the position of limb segments is a highly specialised proprioceptive function important for control of movement. Abnormal knee proprioception has been found in association with several musculoskeletal pathologies but whether nociceptive Stimulation can produce these proprioceptive changes is unclear. This study evaluated the effect of experimentally induced knee pain on knee joint position sense (JPS) in healthy individuals. Study design. Repeated measures, within-subject design. Methods. Knee JPS was tested in 16 individuals with no history of knee pathology under three experimental conditions: baseline control, a distraction task and knee pain induced by injection of hypertonic saline into the infrapatellar fat pad. Knee JPS was measured using active ipsilateral limb matching responses at 20degrees and 60degrees flexion whilst non-weightbearing (NWB) and 20degrees flexion single leg stance. During the tasks, the subjective perception of distraction and severity of pain were measured using 11-point numerical rating scales. Results. Knee JPS was not altered by acute knee pain in any of the positions tested. The distraction task resulted in poorer concentration, greater JPS absolute errors at 20degrees NWB, and greater variability in errors during the WB tests. There were no significant correlations between levels of pain and changes in JPS errors. Changes in JPS with pain and distraction were inversely related to baseline knee JPS variable error in all test positions (r = -0.56 to -0.91) but less related to baseline absolute error. Conclusion. Knee JPS is reduced by an attention-demanding task but not by experimentally induced pain. (C) 2004 Orthopaedic Research Society. Published by Elsevier Ltd. All rights reserved.

Changes in head and neck position affect elbow joint position sense

Changes in the position of the head and neck have been shown to introduce a systematic deviation in the end-point error of an upper limb pointing task. Although previous authors have attributed this to alteration of perceived target location, no studies have explored the effect of changes in head and neck position on the perception of limb position. This study investigated whether changes in head and neck position affect a specific component of movement performance, that is, the accuracy of joint position sense (JPS) at the elbow. Elbow JPS was tested with the neck in four positions: neutral, flexion, rotation and combined flexion/rotation. A target angle was presented passively with the neck in neutral, after a rest period; this angle was reproduced actively with the head and neck in one of the test positions. The potential effects of distraction from head movement were controlled for by performing a movement control in which the head and neck were in neutral for the presentation and reproduction of the target angle, but moved into flexion during the rest period. The absolute and variable joint position errors (JPE) were greater when the target angle was reproduced with the neck in the flexion, rotation, and combined flexion/rotation than when the head and neck were in neutral. This study suggests that the reduced accuracy previously seen in pointing tasks with changes in head position may be partly because of errors in the interpretation of arm position.

Probing three-way interactions in moderated multiple regression:Development and application of a slope difference test

Researchers often use 3-way interactions in moderated multiple regression analysis to test the joint effect of 3 independent variables on a dependent variable. However, further probing of significant interaction terms varies considerably and is sometimes error prone. The authors developed a significance test for slope differences in 3-way interactions and illustrate its importance for testing psychological hypotheses. Monte Carlo simulations revealed that sample size, magnitude of the slope difference, and data reliability affected test power. Application of the test to published data yielded detection of some slope differences that were undetected by alternative probing techniques and led to changes of results and conclusions. The authors conclude by discussing the test's applicability for psychological research. Copyright 2006 by the American Psychological Association.

Canonical solution groups of a homomorphism : manipulator kinematics, nonparametric regression and distributed object systems

The kinematic mapping of a rigid open-link manipulator is a homomorphism between Lie groups. The homomorphisrn has solution groups that act on an inverse kinematic solution element. A canonical representation of solution group operators that act on a solution element of three and seven degree-of-freedom (do!) dextrous manipulators is determined by geometric analysis. Seven canonical solution groups are determined for the seven do! Robotics Research K-1207 and Hollerbach arms. The solution element of a dextrous manipulator is a collection of trivial fibre bundles with solution fibres homotopic to the Torus. If fibre solutions are parameterised by a scalar, a direct inverse funct.ion that maps the scalar and Cartesian base space coordinates to solution element fibre coordinates may be defined. A direct inverse pararneterisation of a solution element may be approximated by a local linear map generated by an inverse augmented Jacobian correction of a linear interpolation. The action of canonical solution group operators on a local linear approximation of the solution element of inverse kinematics of dextrous manipulators generates cyclical solutions. The solution representation is proposed as a model of inverse kinematic transformations in primate nervous systems. Simultaneous calibration of a composition of stereo-camera and manipulator kinematic models is under-determined by equi-output parameter groups in the composition of stereo-camera and Denavit Hartenberg (DH) rnodels. An error measure for simultaneous calibration of a composition of models is derived and parameter subsets with no equi-output groups are determined by numerical experiments to simultaneously calibrate the composition of homogeneous or pan-tilt stereo-camera with DH models. For acceleration of exact Newton second-order re-calibration of DH parameters after a sequential calibration of stereo-camera and DH parameters, an optimal numerical evaluation of DH matrix first order and second order error derivatives with respect to a re-calibration error function is derived, implemented and tested. A distributed object environment for point and click image-based tele-command of manipulators and stereo-cameras is specified and implemented that supports rapid prototyping of numerical experiments in distributed system control. The environment is validated by a hierarchical k-fold cross validated calibration to Cartesian space of a radial basis function regression correction of an affine stereo model. Basic design and performance requirements are defined for scalable virtual micro-kernels that broker inter-Java-virtual-machine remote method invocations between components of secure manageable fault-tolerant open distributed agile Total Quality Managed ISO 9000+ conformant Just in Time manufacturing systems.

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

Statnote 17: using a regression line for prediction and calibration

Two types of prediction problem can be solved using a regression line viz., prediction of the ‘population’ regression line at the point ‘x’ and prediction of an ‘individual’ new member of the population ‘y1’ for which ‘x1’ has been measured. The second problem is probably the most commonly encountered and the most relevant to calibration studies. A regression line is likely to be most useful for calibration if the range of values of the X variable is large, if there is a good representation of the ‘x,y’ values across the range of X, and if several estimates of ‘y’ are made at each ‘x’. It is poor statistical practice to use a regression line for calibration or prediction beyond the limits of the data.

Higher-order co-occurrences for exploratory point pattern analysis and decision tree clustering on spatial data

Analyzing geographical patterns by collocating events, objects or their attributes has a long history in surveillance and monitoring, and is particularly applied in environmental contexts, such as ecology or epidemiology. The identification of patterns or structures at some scales can be addressed using spatial statistics, particularly marked point processes methodologies. Classification and regression trees are also related to this goal of finding "patterns" by deducing the hierarchy of influence of variables on a dependent outcome. Such variable selection methods have been applied to spatial data, but, often without explicitly acknowledging the spatial dependence. Many methods routinely used in exploratory point pattern analysis are2nd-order statistics, used in a univariate context, though there is also a wide literature on modelling methods for multivariate point pattern processes. This paper proposes an exploratory approach for multivariate spatial data using higher-order statistics built from co-occurrences of events or marks given by the point processes. A spatial entropy measure, derived from these multinomial distributions of co-occurrences at a given order, constitutes the basis of the proposed exploratory methods. © 2010 Elsevier Ltd.

Paths of the least resistance:understanding how motives form in international retail joint venturing

Developing the premise that strategies are forged through an ongoing mutual process of developing motives and responses to multiple degrees of resistance, this paper examines the motives underpinning the adoption of joint venture strategies using empirical details from four British retail firms. The findings point to multiple motives forming from multiple paths of resistance in the foreign market, but also among individuals within the firm as well as across the whole international programme. Moreover, this study reveals a paradoxical tension between management's operational impatience to immediately ground the retail format and an overall wariness or gloomy perceptions associated with adopting an international retail joint venture. The paper therefore concludes that the motives and barriers are manifestations of the struggles involved in internationalising retail operations.

Local-Median Method of Forecasting for Regression Time Series under Outliers

2002 Mathematics Subject Classification: 62M20, 62-07, 62J05, 62P20.

Application of the D-Fullness Technique for Breakdown Point Study of the Trimmed Likelihood Estimator to a Generalized Logistic Model

2000 Mathematics Subject Classification: 62J12, 62F35