scholarly journals Parametric bootstrap estimators for hybrid inference in forest inventories

2017 ◽  
Vol 91 (3) ◽  
pp. 354-365 ◽  
Author(s):  
Mathieu Fortin ◽  
Rubén Manso ◽  
Robert Schneider
Keyword(s):  
Multiple Imputation ◽  
Nonlinear Models ◽  
Parametric Bootstrap ◽  
Simulation Studies ◽  
Variance Estimator ◽  
Resampling Methods ◽  
Forest Inventories ◽  
Point Estimator ◽  
Complex Models ◽  
High Level

Abstract In forestry, the variable of interest is not always directly available from forest inventories. Consequently, practitioners have to rely on models to obtain predictions of this variable of interest. This context leads to hybrid inference, which is based on both the probability design and the model. Unfortunately, the current analytical hybrid estimators for the variance of the point estimator are mainly based on linear or nonlinear models and their use is limited when the model reaches a high level of complexity. An alternative consists of using a variance estimator based on resampling methods (Rubin, D. B. (1987). Multiple imputation for nonresponse surveys. John Wiley & Sons, Hoboken, New Jersey, USA). However, it turns out that a parametric bootstrap (BS) estimator of the variance can be biased in contexts of hybrid inference. In this study, we designed and tested a corrected BS estimator for the variance of the point estimator, which can easily be implemented as long as all of the stochastic components of the model can be properly simulated. Like previous estimators, this corrected variance estimator also makes it possible to distinguish the contribution of the sampling and the model to the variance of the point estimator. The results of three simulation studies of increasing complexity showed no evidence of bias for this corrected variance estimator, which clearly outperformed the BS variance estimator used in previous studies. Since the implementation of this corrected variance estimator is not much more complicated, we recommend its use in contexts of hybrid inference based on complex models.

scholarly journals Information criteria for nonlinear time series models

2016 ◽  
Vol 20 (3) ◽  
Author(s):  
Saskia Rinke ◽  
Philipp Sibbertsen
Keyword(s):  
Error Term ◽  
Linear Models ◽  
Nonlinear Models ◽  
General Information ◽  
Information Criteria ◽  
Order Selection ◽  
Simulation Studies ◽  
Variance Estimator ◽  
Linear And Nonlinear ◽  
The Impact

AbstractIn this paper the performance of different information criteria for simultaneous model class and lag order selection is evaluated using simulation studies. We focus on the ability of the criteria to distinguish linear and nonlinear models. In the simulation studies, we consider three different versions of the commonly known criteria AIC, SIC and AICc. In addition, we also assess the performance of WIC and evaluate the impact of the error term variance estimator. Our results confirm the findings of different authors that AIC and AICc favor nonlinear over linear models, whereas weighted versions of WIC and all versions of SIC are able to successfully distinguish linear and nonlinear models. However, the discrimination between different nonlinear model classes is more difficult. Nevertheless, the lag order selection is reliable. In general, information criteria involving the unbiased error term variance estimator overfit less and should be preferred to using the usual ML estimator of the error term variance.

scholarly journals Multiple-Imputation Variance Estimation in Studies With Missing or Misclassified Inclusion Criteria

2020 ◽  
Vol 189 (12) ◽  
pp. 1628-1632
Author(s):  
Mark J Giganti ◽  
Bryan E Shepherd
Keyword(s):  
Multiple Imputation ◽  
Variance Estimation ◽  
Variance Estimator ◽  
Inclusion Criteria ◽  
Variance Estimators ◽  
Coverage Probabilities ◽  
Log Odds ◽  
Variance Estimate ◽  
High Level ◽  
Analysis Models

Abstract In observational studies using routinely collected data, a variable with a high level of missingness or misclassification may determine whether an observation is included in the analysis. In settings where inclusion criteria are assessed after imputation, the popular multiple-imputation variance estimator proposed by Rubin (“Rubin’s rules” (RR)) is biased due to incompatibility between imputation and analysis models. While alternative approaches exist, most analysts are not familiar with them. Using partially validated data from a human immunodeficiency virus cohort, we illustrate the calculation of an imputation variance estimator proposed by Robins and Wang (RW) in a scenario where the study exclusion criteria are based on a variable that must be imputed. In this motivating example, the corresponding imputation variance estimate for the log odds was 29% smaller using the RW estimator than using the RR estimator. We further compared these 2 variance estimators with a simulation study which showed that coverage probabilities of 95% confidence intervals based on the RR estimator were too high and became worse as more observations were imputed and more subjects were excluded from the analysis. The RW imputation variance estimator performed much better and should be employed when there is incompatibility between imputation and analysis models. We provide analysis code to aid future analysts in implementing this method.

scholarly journals Analysis power shortage minimization methods in the modern processing software for adequacy assessment of electric power systems

2020 ◽  
Vol 209 ◽  
pp. 06008
Author(s):  
Dmitrii Iakubovskii ◽  
Dmitry Krupenev
Keyword(s):  
Power Systems ◽  
Nonlinear Models ◽  
Mathematical Optimization ◽  
Optimization Methods ◽  
Point Of View ◽  
Software Systems ◽  
Minimization Methods ◽  
Adequacy Assessment ◽  
Commercial Solver ◽  
High Level

Analysis of domestic and foreign software systems for assessing the resource adequacy showed a variety of models and methods used in them. Many software systems use both linear and nonlinear models, these models are optimized according to various criteria to simulate the operation of the system. As tools for solving, software usually use commercial high-level modelling systems for mathematical optimization. However, in addition to the existing ready-made commercial solutions, the authors consider the effectiveness of optimization methods, as well as their parallelized versions, which can be independently implemented and applied as a solver for a specific problem. As a result, it was confirmed that these methods can be used to solve the problem, but they are less effective relative to a commercial solver. From the point of view of accuracy and resources spent on calculations, the most effective of the independently implemented methods turned out to be the parallelized method of differential evolution, which was confirmed by numerical experiments on small systems.

Prediction of Finite Population Proportion When Responses Are Misclassified

2020 ◽  
Author(s):  
Sumanta Adhya ◽  
Surupa Roy ◽  
Tathagata Banerjee
Keyword(s):  
Empirical Study ◽  
Finite Population ◽  
Asymptotic Properties ◽  
Auxiliary Variable ◽  
Binary Response ◽  
Simulation Studies ◽  
Variance Estimator ◽  
Computationally Efficient ◽  
Extensive Simulation ◽  
Population Proportion

Abstract We propose a model-based predictive estimator of the finite population proportion of a misclassified binary response, when information on the auxiliary variable(s) is available for all units in the population. Asymptotic properties of the misclassification-adjusted predictive estimator are also explored. We propose a computationally efficient bootstrap variance estimator that exhibits better performance compared to usual analytical variance estimator. The performance of the proposed estimator is compared with other commonly used design-based estimators through extensive simulation studies. The results are supplemented by an empirical study based on literacy data.

Basic mathematical imputation techniques

2016 ◽  
Vol 61 (9) ◽  
pp. 7-54
Author(s):  
Jacek Wesołowski ◽  
Jakub Tarczyński
Keyword(s):  
Multiple Imputation ◽  
Random Variables ◽  
Independent Random Variables ◽  
Original Sample ◽  
Variance Estimator ◽  
Mathematical Background ◽  
Random Mechanism ◽  
Starting Point

The article presents the basics of imputation methodology (including the methodology of multiple imputation), focusing on understanding its mathematical background. We analyze the situation when observations in the original sample are independent random variables with identical distributions, and response or its lack is modeled by a random mechanism which is independent of observations. In particular, we point out to problems that arise when the standard Rubin estimate of the multiple imputation variance estimator is used. A possible improvement of this popular estimator is indicated. The starting point of the analysis is when the appearance of response deficiencies is caused by a deterministic mechanism.

scholarly journals OpenAlea: a visual programming and component-based software platform for plant modelling

2008 ◽  
Vol 35 (10) ◽  
pp. 751 ◽  
Author(s):  
Christophe Pradal ◽  
Samuel Dufour-Kowalski ◽  
Frédéric Boudon ◽  
Christian Fournier ◽  
Christophe Godin
Keyword(s):  
Architectural Design ◽  
Computer Modelling ◽  
Visual Programming ◽  
General Purpose ◽  
Script Language ◽  
Heterogeneous Model ◽  
Complex Models ◽  
Plant Modelling ◽  
Model Components ◽  
High Level

The development of functional–structural plant models requires an increasing amount of computer modelling. All these models are developed by different teams in various contexts and with different goals. Efficient and flexible computational frameworks are required to augment the interaction between these models, their reusability, and the possibility to compare them on identical datasets. In this paper, we present an open-source platform, OpenAlea, that provides a user-friendly environment for modellers, and advanced deployment methods. OpenAlea allows researchers to build models using a visual programming interface and provides a set of tools and models dedicated to plant modelling. Models and algorithms are embedded in OpenAlea ‘components’ with well defined input and output interfaces that can be easily interconnected to form more complex models and define more macroscopic components. The system architecture is based on the use of a general purpose, high-level, object-oriented script language, Python, widely used in other scientific areas. We present a brief rationale that underlies the architectural design of this system and we illustrate the use of the platform to assemble several heterogeneous model components and to rapidly prototype a complex modelling scenario.

On the bias of the multiple-imputation variance estimator in survey sampling

2006 ◽  
Vol 68 (3) ◽  
pp. 509-521 ◽  
Author(s):  
Jae Kwang Kim ◽  
J. Michael Brick ◽  
Wayne A. Fuller ◽  
Graham Kalton
Keyword(s):  
Multiple Imputation ◽  
Survey Sampling ◽  
Variance Estimator

scholarly journals Study of the stress-strain state of reinforced geosynthetic material or the foundation of the bored foundation of the bridge

2019 ◽  
Vol 6 (4) ◽  
Author(s):  
Sergey Kudryavtsev ◽  
Tatiana Valtseva ◽  
Vyacheslav Shemyakin ◽  
Yuliya Bugunova ◽  
Zhanna Kotenko
Keyword(s):  
Bearing Capacity ◽  
Building Materials ◽  
Nonlinear Models ◽  
Far East ◽  
Soil Mass ◽  
Operational Reliability ◽  
Climatic Conditions ◽  
Stable Operation ◽  
Rational Solutions ◽  
High Level

The building of constructions in northern regions of the Far East is always connected with a high degree of seasonal freezing risk. This especially refers to a line transport structures which require a high level of reliability and responsibility. Such structures should provide permissible deformability and bearing capacity of the bases when exposed to promising moving loads in difficult geological and climatic conditions. The article discusses the study of the foundations of bored foundations of bridges using methods of mathematical modeling and geosynthetic materials. The study used standard and numerical calculation methods to determine the rational parameters of structural elements and the degree of their operational reliability and durability. In determining the behavior of structures as a whole with the joint interaction of their individual elements with each other, nonlinear models of the soil of the base of the structures were used. Numerical modeling of bored foundations in an elasto-plastic soil mass allowed us to develop effective structural solutions to reduce the deformability of the bridge and increase the bearing capacity of the pile foundation due to reinforcing measures during the construction of the grillage and the creation of rational parameters of the structure as a whole. One of the rational solutions for the main issues which is connected with a construction of facilities in the areas with complex geological and climatic conditions is reasonable usage of modern geosynthetic material properties. Such materials are capable of providing long-term stable operation of facilities made of local building materials. So, the properties of such geosynthetics materials must fully comply with the demands of conditions of their work in the structures and provide a long lifespan as well as high quality.

Wind assisted propulsion systems and the role of a Ship Classification Society

2019 ◽  
Author(s):  
U Hollenbach ◽  
H Hoffmeister ◽  
J Wienke
Keyword(s):  
Third Party ◽  
Simulation Studies ◽  
Propulsion Systems ◽  
Technical Standards ◽  
Limit Values ◽  
Rule Set ◽  
Significant Measure ◽  
Ship Classification ◽  
High Level

As an independent third-party consultant, DNV GL provides dedicated simulation studies on comparing the performance, reliability and economic impact of different sailing rig concepts in a high-level assessment. In more detailed studies a comparison of the reduction of green-house gases on different shipping routes throughout the year can be assessed. Each newbuilding must fulfil mandatory EEDI limit values. What is almost unknown in the shipbuilding community is that wind propulsion systems can become a significant measure to fulfil future stricter limits. EEDI rules and regulations offer the possibility considering the effect of WAPS (Wind Assisted Propulsions Systems) in the EEDI calculation. The assumptions in the EEDI rule set regarding a global wind matrix with reference to the global shipping routes are explained and discussed. DNV GL has traditionally been dealing with certification and engineering of sailing rigs and uses these synergies for offering certification and engineering services within the wind propulsion segment. Recently technical standards for wind assisted propulsion systems and a new additional class notation for the ships carrying such devices has been developed. These services and standards are presented in the third part of the paper.

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