Variance Tracking Research Articles

Bayesian approximation for parameterized KALMAN filter for investigation and simulation of unknown noise variance trajectory following in state space models with different noise distributions

Bayesian approach can be used for parameter identification and extraction in state space models and its ability for analyzing sequence of data in dynamical system is proved in different literatures. In this paper, Bayesian approach for approximation of variances in measurement noise with KALMAN filter is applied for estimation of the dynamical state and measurement data in discrete dynamical system. Detection of uncertainty and estimation of those can be done simultaneously with adaptive KALMAN filter. This algorithm at each step time estimates noise variance and state of system with KALMAN filter. Then, approximation is formed at each step separately and at each step sufficient statistics of the state and noise variances are computed with a fixed-point iteration of a KALMAN filter. For showing influence of variance in measurement data on algorithm different simulations is applied. First, effect of variance and its distribution on detection performance is simulated in KALMAN filter without Bayesian formulation. Then simulation is applied to KALMAN filter with ability of variance tracking of measurement data.in these simulations, influence of distribution of measurement data in each step is estimated and true variance of data is obtained by algorithm and is compared in different scenarios. Afterwards, one typical modeling of nonlinear state space model with inducing noise measurement is simulated by this approach. Finally, the performance and the important limitations of this algorithm in these simulations are explained.

When trackers are aware of ESG: Do ESG ratings matter to tracking error portfolio performance?

With the increasing severity of the greenhouse effect and environmental pollution, environmental, social, and governance (ESG) investing has received much attention in recent years. This paper studies how ESG scores and investors’ ESG preferences affect the performance of tracking portfolios. We embed ESG information and the ESG preferences of investors into the mean–variance tracking error model, and then explicitly solve the new tracking portfolio model. The theoretical analysis shows that ESG information can improve the expected returns, information ratio (IR) and other performance metrics of tracking portfolios. The relationship between the ESG scores and IR of tracking portfolios is represented by an inverse U-type ESG-IR frontier. Consistent with theoretical predictions, numerical results with a real market benchmark show that ESG information and ESG investor preference have a positive impact on the realized returns, IR, net aggregate returns and cumulative returns of tracking portfolios. Our results provide investors with several valuable references about ESG awareness and preferences.

Real-time Subsurface Control Variates

Real-time adaptive sampling is a new technique recently proposed for efficient importance sampling in realtime Monte Carlo sampling in subsurface scattering. It adaptively places samples based on variance tracking to help escape the uncanny valley of subsurface rendering. However, the occasional performance drop due to temporal lighting dynamics (e.g., guns or lights turning on and off) could hinder adoption in games or other applications where smooth high frame rate is preferred. In this paper we propose a novel usage of Control Variates (CV) in the sample domain instead of shading domain to maintain a consistent low pass time. Our algorithm seamlessly reduces to diffuse with zero scattering samples for sub-pixel scattering. We propose a novel joint-optimization algorithm for sample count and CV coefficient estimation. The main enabler is our novel time-variant covariance updating method that helps remove the effect of recent temporal dynamics from variance tracking. Since bandwidth is critical in real-time rendering, a solution without adding any extra textures is also provided.

Regression Function and Noise Variance Tracking Methods for Data Streams with Concept Drift

Abstract Two types of heuristic estimators based on Parzen kernels are presented. They are able to estimate the regression function in an incremental manner. The estimators apply two techniques commonly used in concept-drifting data streams, i.e., the forgetting factor and the sliding window. The methods are applicable for models in which both the function and the noise variance change over time. Although nonparametric methods based on Parzen kernels were previously successfully applied in the literature to online regression function estimation, the problem of estimating the variance of noise was generally neglected. It is sometimes of profound interest to know the variance of the signal considered, e.g., in economics, but it can also be used for determining confidence intervals in the estimation of the regression function, as well as while evaluating the goodness of fit and in controlling the amount of smoothing. The present paper addresses this issue. Specifically, variance estimators are proposed which are able to deal with concept drifting data by applying a sliding window and a forgetting factor, respectively. A number of conducted numerical experiments proved that the proposed methods perform satisfactorily well in estimating both the regression function and the variance of the noise.

Random Error Analysis of MEMS Gyroscope Based on an Improved DAVAR Algorithm

In view that traditional dynamic Allan variance (DAVAR) method is difficult to make a good balance between dynamic tracking capabilities and the confidence of the estimation. And the reason is the use of a rectangular window with the fixed window length to intercept the original signal. So an improved dynamic Allan variance method was proposed. Compared with the traditional Allan variance method, this method can adjust the window length of the rectangular window adaptively. The data in the beginning and terminal interval was extended with the inverted mirror extension method to improve the utilization rate of the interval data. And the sliding kurtosis contribution coefficient and kurtosis were introduced to adjust the length of the rectangular window by sensing the content of shock signal in terminal interval. The method analyzed the window length change factor in different stable conditions and adjusted the rectangular window’s window length according to the kurtosis, sliding kurtosis contribution coefficient. The test results show that the more the kurtosis stability threshold was close to 3, the stronger the dynamic tracking ability of DAVAR would be. But the kurtosis stability threshold was too close to 3, there was a misjudgement in kurtosis analysis of signal stability, resulting in distortion of DAVAR analysis results. When using the improved DAVAR method, the kurtosis stability threshold can be close to 3 to improve the tracking ability and the estimation confidence in stable interval. Therefore, it solved the problem that the dynamic Allan variance tracking ability and confidence level were difficult to take into account, and also solved the problem of misjudgement in the stability analysis of kurtosis.

Clinical Pathway for Thyroidectomy

Clinical pathways are care plans applicable to patient care procedures that present variations in practice and a predictable clinical course. They are designed not as a substitute for clinical judgement, but rather as a means to improve the effectiveness and efficiency of the procedures. This clinical pathway is the result of a collaborative work of the Sections of Endocrine Surgery and Quality Management of the Spanish Association of Surgeons. It attempts to provide a framework for standardising the performance of thyroidectomy, the most frequently performed operation in endocrine surgery. Along with the usual documents of clinical pathways (temporary matrix, variance tracking and information sheets, assessment indicators and a satisfaction questionnaire) it includes a review of the scientific evidence around different aspects of pre, intra and postoperative management. Among others, antibiotic and antithrombotic prophylaxis, preoperative preparation in hyperthyroidism, intraoperative neuromonitoring and systems for obtaining hemostasis are included, along with management of postoperative hypocalcemia.

Vía clínica de tiroidectomía

Clinical pathways are care plans applicable to patient care procedures that present variations in practice and a predictable clinical course. They are designed not as a substitute for clinical judgment, but rather as a means to improve the effectiveness and efficiency of the procedures. This clinical pathway is the result of a collaborative work of the Sections of Endocrine Surgery and Quality Management of the Spanish Association of Surgeons. It attempts to provide a framework for standardizing the performance of thyroidectomy, the most frequently performed operation in endocrine surgery. Along with the usual documents of clinical pathways (temporary matrix, variance tracking and information sheets, assessment indicators and a satisfaction questionnaire) it includes a review of the scientific evidence around different aspects of pre, intra and postoperative management. Among others, antibiotic and antithrombotic prophylaxis, preoperative preparation in hyperthyroidism, intraoperative neuromonitoring and systems for obtaining hemostasis are included, along with management of postoperative hypocalcemia.

NYS Workers’ Compensation Medical Treatment Guidelines: Variance Tracking and Guidelines Amendment Program

In December of 2010 the New York State Insurance Department drafted medical treatment guidelines, including those for the care of the back and neck, utilizing input from physicians who were representatives of labor unions or medical directors of workers’ compensation carriers. None of the members of the task force were orthoapedic surgeons nor neurosurgeons.

Clinical pathways: Adherence issues in complex older female patients with heart failure (HF)

HF is a leading health care concern, often under-recognized and under-treated in older women. Management of this complex condition frequently requires a multidisciplinary approach and a clinical pathway can be used to deliver coordinated care. This report is based on the intervention/treatment arm ( n = 45) of a randomized controlled trial in older women who participated in a multidisciplinary clinic. We describe the development of a clinical pathway for HF and the variance reporting including factors affecting adherence with the pathway. Variances are patient or staff actions that did not meet the expected outcomes. Of the 45 intervention arm female patients, 5 were able to fully complete the program, meaning that all of the intended 12 visits were completed successfully. Thirteen women missed more than three clinic visits, and the rest attended most visits. Variance tracking identified that visits were interrupted most often by patient-related health issues, such as fatigue and pain, which may not be surprising given the expected multiple co-morbidities in this population. Transportation problems were identified as a barrier to attendance. Our study demonstrates that a clinical pathway can be implemented in an older, female population with HF. This report identifies some of the challenges and provides future recommendations for prospective pathway development.

The Impact of Standardized Order Sets and Intensive Clinical Case Management on Outcomes in Community-Acquired Pneumonia

Community-acquired pneumonia is a frequent cause for hospital admission that results in significant costs to the health care system. The length of hospital stay (LOS) affects costs as well as risk for nosocomial medical complications. The purpose of this study was to test whether the addition of intensive clinical case management to clinical guidelines could lead to a reduction in LOS that was not achievable by guidelines alone, while maintaining quality of care. Patients were studied in 3 sequential blocks at a single hospital from November 2002 to February 2005. Block 1 patients (n = 110) were given conventional treatment. For block 2 (n = 119), guidelines and/or standardized order sets (SOSs) were used supported by intensive clinical case management (ICCM) (full variance tracking with concurrent feedback and reminders). The ICCM interventions were conducted by resident physicians. For block 3 (n = 115), all orders were written with guidelines and/or SOSs but without ICCM. The mean +/- SD time to clinical stability was not significantly different between the groups (block 1, 3.3 +/- 1.4 days; block 2, 3.2 +/- 1.2 days; and block 3, 3.4 +/- 1.3 days). The mean LOS was significantly lower in block 2 (5.3 +/- 3.5 days) than in blocks 1 (8.8 +/- 4.4 days) (P<.001) and 3 (7.3 +/- 3.9 days) (P<.01) and significantly lower in block 3 than in block 1 (P = .05). Time to change to oral antibiotics was earlier in block 2 (3.7 +/- 0.9 days) than in blocks 1 and 3 (5.7 +/- 2.4 and 5.0 +/- 1.9 days, respectively) (P<.001). The mean time from clinical stability to hospital discharge was significantly shorter for block 2 (2.1 +/- 2.2 days) than for blocks 1 (5.3 +/- 4.4 days) (P<.001) and 3 (4.9 +/- 4.2 days) (P<.001). Patients in block 2 had a greater proportion with progressive ambulation (P<.001), pneumococcal (P<.001) or influenza vaccination (P<.01), deep-venous thrombosis prophylaxis (P = .01), and smoking cessation counseling (P = .01). There was no significant difference between the blocks in mortality or hospital readmission rate. The combined intervention of SOS plus ICCM led to a substantial reduction in LOS while maintaining quality of care. The main effect occurred by reducing the time from clinical stability to discharge, which appeared to be the key "modifiable" process of care adding to a prolonged LOS.

Maximum likelihood estimation of the Heston stochastic volatility model using asset and option prices: an application of nonlinear filtering theory

Let us suppose that the dynamics of the stock prices and of their stochastic variance is described by the Heston model, that is by a system of two stochastic differential equations with a suitable initial condition. The aim of this paper is to estimate the parameters of the Heston model and one component of the initial condition, that is the initial stochastic variance, from the knowledge of the stock and option prices observed at discrete times. The option prices considered refer to an European call on the stock whose prices are described by the Heston model. The method proposed to solve this problem is based on a filtering technique to construct a likelihood function and on the maximization of the likelihood function obtained. The estimated parameters and initial value component are characterized as being a maximizer of the likelihood function subject to some constraints. The solution of the filtering problem, used to construct the likelihood function, is based on an integral representation of the fundamental solution of the Fokker–Planck equation associated to the Heston model, on the use of the wavelet expansions presented in (Fatone et al. in High performance algorithms based on a new wavelet expansion for time dependent acoustic obstacle scattering. Commun. Computat. Phys. (2007), Research Developments in Acoustics, vol. 2, pp. 39–69. Transworld Research Network, Kerala (2005), New wavelet bases made of piecewise polynomial functions: approximation theory, quadrature rules and applications to kernel sparsification and image compression. SIAM J. Sci. Comput. (submitted)) to approximate the integral kernel appearing in the representation formula of the fundamental solution, on a simple truncation procedure to exploit the sparsifying properties of the wavelet expansions and on the use of the fast Fourier transform (FFT). The use of these techniques generates a very efficient and fully parallelizable numerical procedure to solve the filtering problem, this last fact makes possible to evaluate very efficiently the likelihood function and its gradient. As a byproduct of the solution of the filtering problem we have developed a stochastic variance tracking technique that gives very good results in numerical experiments. The maximum likelihood problem used in the estimation procedure is a low dimensional constrained optimization problem, its solution with ad hoc techniques is justified by the computational cost of evaluating the likelihood function and its gradient. We use parallel computing and a variable metric steepest ascent method to solve the maximum likelihood problem. Some numerical examples of the estimation problem using synthetic and real data, that is data relative to an index of the Milano stock exchange (S&PMIB30), obtained with a parallel implementation of the previous numerical method are presented. Very impressive speed up factors are obtained in the numerical examples using the parallel implementation of the numerical method proposed. The website: http://www.econ.univpm.it/pacelli/mariani/finance/w1 contains animations and some auxiliary material that helps the understanding of this paper and makes available to the interested users the computer programs used to produce the numerical experience presented.

Optimal tracking design for stochastic fuzzy systems

In general, fuzzy control design for stochastic nonlinear systems is still difficult since the fuzzy bases are stochastic so as to increase the difficulty and complexity of the fuzzy tracking control design. In this study, a fuzzy stochastic moving-average model with control input (fuzzy ARMAX model) is introduced to describe nonlinear stochastic systems. From the fuzzy ARMAX model, a fuzzy one-step ahead prediction model is developed. Based on a fuzzy one-step ahead prediction stochastic model, optimal design algorithms are proposed to achieve the optimal tracking of nonlinear stochastic systems. In this study, the minimum variance tracking control, generalized minimum variance tracking control, and the optimal model reference tracking control are developed for stochastic fuzzy systems. We construct some basic stability conditions for general stochastic fuzzy systems and use these conditions to verify the stability of the fuzzy tracking control systems. Finally, two simulation examples are given to indicate the performance of the proposed methods.

Pathways for continence care: an audit to assess how they are used.

This is a follow-up article to three articles that were published between 2000 and 2001 in the British Journal of Nursing about the development of template pathways for continence care (Bayliss et al, 2000a,b, 2001). It reports on what has happened since the development of these templates. One hundred and forty-four healthcare professionals working in the field of continence care were asked to complete a questionnaire about whether the pathways are being used and what changes have been made to them. The audit found nearly half of the respondents are currently using the pathways and find them an effective method of assessing incontinence and providing equitable quality of care for patients. Many respondents have made changes to the pathways, making them easier to use and adapting them to local practice and the availability of local resources. This was what was anticipated, although the authors noted that variance tracking, which should be the driver for change, had not significantly influenced local pathways. Of those healthcare professionals not using pathways, all said they were still interested in using them, which is particularly encouraging as pathways are promoted in 'Guidelines for Continence Care' (Department of Health, 2000). To provide support to these individuals and encourage the efforts of those already using the pathways, a support group is to be established following a further conference on pathways for continence care later this year. It will be the role of this group to facilitate information sharing on pathway development. As a first step in the dissemination of information, a pack is being produced comprising consolidated versions of the changes to the pathways used in practice all over the country.

Using variance tracking to improve outcomes and reduce costs

Clinical pathways outline patient-care delivery over time for specific patient populations, but their true utility is derived from information obtained through variance tracking-documenting when and why a patient's care varies from the clinical pathway. This article describes one health care facility's variance tracking for pulmonary, medical oncology, and nephrology patients and their associated measured outcomes. Avoidable hospital days were tracked and a performance improvement initiative, focused on the pathways most often used on the medical unit, was undertaken, resulting in decreased length of patient stay and cost savings of more than $160,000.

Lessons Learned in the Process of Stroke Quality Management: Revised tools and strategies in a follow-up study

P229 Objectives Written care protocols and quality improvement efforts have recently been included in published guidelines on care of the ischemic stroke patient. We describe revisions to the quality management process that resulted in increased protocol use at a 469-bed medical school affiliate private hospital. Methods An earlier clinical pathway for ischemic stroke was ineffectively implemented as shown by pathway use in less than half of appropriate cases. A multidisciplinary team addressed barriers identified in that early experience to modify strategies in the development of a new set of quality management tools (QMT) for ischemic stroke. The revised QMT included: standing orders, clinical pathway, NIH Stroke Scale flow sheet, diagnostic summary form, and variance tracking tool. QMT use rates were calculated by medical record abstraction during a 3-month pilot study and physician and nurse usage rates determined. Factors contributing to QMT usage were analyzed. Results Twenty-eight ischemic stroke patients were admitted to the pilot unit during the study. Usage rates for components of the QMT driven by physicians were: standing orders 93%; IV tPA standing orders 100%; and diagnostic summary form 46%. Nurse related QMT usage was: clinical pathway 96%; NIH Stroke Scale flow sheet 75%; and variance tracking tool 75%. Key strategies that contributed to improved implementation were: 1) early involvement and continuous communication between the expanded multidisciplinary team, staff nurses and physicians 2) empowerment of nurses through NIH Stroke Scale training 3) perception of mutual accountability between nurses and physicians through use of QMT documents 4) clearly defined administrative directives. Conclusion Effective implementation of quality management protocols for ischemic stroke requires active participation of related disciplines at working levels, clear administrative support, and mutual accountability of physicians and nurses. Continuous critical appraisal of the process can afford eventual strategic solutions.

Lessons Learned in the Process of Stroke Quality Management: Revised tools and strategies in a follow-up study

P229 Objectives Written care protocols and quality improvement efforts have recently been included in published guidelines on care of the ischemic stroke patient. We describe revisions to the quality management process that resulted in increased protocol use at a 469-bed medical school affiliate private hospital. Methods An earlier clinical pathway for ischemic stroke was ineffectively implemented as shown by pathway use in less than half of appropriate cases. A multidisciplinary team addressed barriers identified in that early experience to modify strategies in the development of a new set of quality management tools (QMT) for ischemic stroke. The revised QMT included: standing orders, clinical pathway, NIH Stroke Scale flow sheet, diagnostic summary form, and variance tracking tool. QMT use rates were calculated by medical record abstraction during a 3-month pilot study and physician and nurse usage rates determined. Factors contributing to QMT usage were analyzed. Results Twenty-eight ischemic stroke patients were admitted to the pilot unit during the study. Usage rates for components of the QMT driven by physicians were: standing orders 93%; IV tPA standing orders 100%; and diagnostic summary form 46%. Nurse related QMT usage was: clinical pathway 96%; NIH Stroke Scale flow sheet 75%; and variance tracking tool 75%. Key strategies that contributed to improved implementation were: 1) early involvement and continuous communication between the expanded multidisciplinary team, staff nurses and physicians 2) empowerment of nurses through NIH Stroke Scale training 3) perception of mutual accountability between nurses and physicians through use of QMT documents 4) clearly defined administrative directives. Conclusion Effective implementation of quality management protocols for ischemic stroke requires active participation of related disciplines at working levels, clear administrative support, and mutual accountability of physicians and nurses. Continuous critical appraisal of the process can afford eventual strategic solutions.

Rapid Progression Following Cardiac Surgery

This article examines one institution's transition into rapid progression after cardiac surgery. This includes clinical guidelines and the integral use of outcomes measures to govern care. Fast-track initiatives are examined in the scope of cost containment. A comprehensive, multidisciplinary approach is emphasized throughout.

Impact on process of trauma care delivery 1 year after the introduction of a trauma program in a provincial trauma center.

Trauma care delivery in Canada, even in major trauma centers, usually devolves to the most involved service. For patients with multisystem injuries, this is not always optimal and aspects of care outside the domain of the primary service are apt to be overlooked. Trauma care is necessarily multidisciplinary, and to be optimal, appropriate integration of the care process and prioritization are required. The purpose of this study was to examine the impact on care in a busy provincial trauma center, after the introduction of a trauma program with a clinical trauma service, revised trauma protocols, and a dedicated trauma unit. Data were collected prospectively before and during the introduction of the program. Aspects of care studied included trauma patient volume, compliance with trauma team activation and trauma consultation protocols, delays to the operating room for hypotension or open fractures, delays in disposition to the unit, average length of stay, and mortality based on Trauma and Injury Severity Score analysis. Data are presented summarized by quarter, one before and four after the introduction of the program. Variance tracking was introduced before the last quarter. Differences between preprogram and postprogram performance were assessed by using analysis of variance (asterisks indicates p < 0.05 compared with preprogram performance). Trauma unit average length of stay decreased from 10.15 days initially to 9.66 and 9.14* days at 6 and 12 months, reducing costs. Improved survival was demonstrated by Trauma and Injury Severity Score methodology with z score achieving significance compared with Major Trauma Outcome Study outcomes after program implementation. Trauma care improvement can be achieved by a multidisciplinary team focusing on the process of care, developing a dedicated trauma service to manage the more seriously injured patients, collecting them onto a single unit, and initiating program management.

Global Asset Allocation with Multirisk Considerations

Multirisk asset allocations help investors optimally balance their desire for expected return with their aversion to two types of risk—absolute volatility and tracking error relative to a benchmark. Zhang empirically tests a multirisk optimization model by allocating funds among global equity markets. The results suggest that mean– variance tracking error optimization may provide more efficient portfolios than the traditional approach of mean–variance with constraints.

Spine update. Clinical pathways.

Health care providers are becoming increasingly involved with the development of clinical pathways as they take on more of the responsibilities of quality management and resource use. Although clinical pathways that are developed at the national, regional, or specialty organization level provide a framework for reference, locally developed pathways tailor care to patients who are served within an agency or community. As multidisciplinary teams develop pathways for patients with back and spine disorders, they create tangible definitions of quality. Variance tracking systems used in conjunction with pathways provide feedback on patient progress and outcomes. These guidelines have significant potential for the future.