THE DESIGN AND ANALYSIS OF EXPERIMENTS. By Oscar Kempthorne. New York, John Wiley and Sons, Inc., 1952. 631 pp. $8.50. This book by a teacher of statistics (as well as a consultant for \"experimenters\") is a comprehensive study of the philosophical background for the statistical design of experiment. It is necessary to have some facility with algebraic notation and manipulation to be able to use the volume intelligently. The problems are presented from the theoretical point of view, without such practical examples as would be helpful for those not acquainted with mathematics. The mathematical justification for the techniques is given. As a somewhat advanced treatment of the design and analysis of experiments, this volume will be interesting and helpful for many who approach statistics theoretically as well as practically. With emphasis on the \"why,\" and with description given broadly, the author relates the subject matter to the general theory of statistics and to the general problem of experimental inference. MARGARET J. ROBERTSON

The Design and Analysis of Experiments

计量经济分析 = Econometric analysis

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

https://www.ece.lsu.edu/mcu/lawss/add_materials/FaultDetectionPart1.pdf

A Review of Process Fault Detection and Diagnosis Part I : Quantitative Model-Based Methods

A review of process fault detection and diagnosis: Part III: Process history based methods

http://www.nt.ntnu.no/users/skoge/prost/proceedings/dycops2013-and-cab2013/media/DYCOPS/files/0164.pdf

Linear Machine: A Novel Approach to Point Location Problem

A solar thermal power plant presents an environmentally friendly process for producing power. However, due to diurnal and seasonal variations in the availability of solar radiation, as well as unce...

Dynamic Modeling and Simulation of a Hybrid Solar Thermal Power Plant

Constraint programming and genetic algorithm

Moving horizon estimation (MHE) has emerged as a popular technique for state estimation of nonlinear dynamical systems. A key parameter in MHE is the arrival cost that links the formulation in the current horizon with the past data. Most approaches available in literature use additional filters, such as extended Kalman filter or unscented Kalman filter to obtain the covariance matrix used in the arrival cost. In this work, we propose conceptually simple, alternate ways for obtaining the covariances of the arrival cost. Our approaches are motivated by parameter estimation in nonlinear regression. We view the MHE problem as a nonlinear regression problem with the states being the unknown parameters of the regression problem. The covariance of these estimated parameters can then be computed based on the Jacobian matrix. We also propose a Monte-Carlo based sampling approach for covariance calculation. This approach avoids Jacobian matrix calculation but is computationally intensive. A third approach utilizing approximate Hessian, based on equivalence between nonlinear regression and maximum likelihood estimation, is also proposed. Thus, the proposed approaches are able to compute the arrival cost without requiring any other external filter implementation. The MHE estimation performances obtained with the arrival cost covariances computed using the proposed approaches are compared with extended Kalman filter (EKF) and EKF based MHE implementation on case studies taken from literature. These comparisons demonstrate the utility of the proposed approaches.

Covariance computation in MHE: A nonlinear regression approach

The South Asian monsoon (SAM) is critical to the agricultural economy of the region. Large-scale processes affecting the monsoon have been traditionally been well studied; however, much less is known about the role of local processes, especially one governed by levels of atmospheric aerosols, or the mix of pollutant particles and dust. This chapter delineates the aerosol influence on cloud modification and short-term rainfall inhibition over India, employing observational data for the period of 2000–2009. Aerosols can change cloud-related properties in contrasting ways in years of deficient and abundant monsoon. In deficient years, increased levels of atmospheric aerosols correlate with smaller cloud drops, shallower cloud heights, and less cloud-ice formation. In contrast, in abundant rainfall years, higher levels of aerosols correlate with larger cloud droplet size, taller clouds, and greater ice-cloud formation. Further, causality was established in high aerosol and low rainfall regions spanning across the Indian subcontinent, wherein enhancement in aerosol levels caused suppression of daily precipitation anomaly multiple times in a monsoon season with lags of a few days. The studies also suggest aerosol effects on increases in the frequency and length of monsoon breaks, with implications for rainfall deficit and food grain production. This work makes important linkages between enhanced air pollution and perturbations in the timing and short-term suppression of regional monsoon rainfall, implying the need for greater synergy in policies addressing air pollution and climate change.

Mani Bhushan

Papers

Linear Machine: A Novel Approach to Point Location Problem

Dynamic Modeling and Simulation of a Hybrid Solar Thermal Power Plant

Constraint programming and genetic algorithm

Covariance computation in MHE: A nonlinear regression approach

Aerosol Influences on Cloud Modification and Rainfall Suppression in the South Asian Monsoon Region