scholarly journals A parametric model for estimating nuptiality patterns in modern populations

2015 ◽  
Vol 42 (1-2) ◽  
pp. 130 ◽  
Author(s):  
Anastasia Kostaki ◽  
Paraskevi Peristera
Keyword(s):  
Mixture Models ◽  
Parametric Model ◽  
Parametric Models ◽  
Human Populations ◽  
Marriage Rates ◽  
First Marriage ◽  
Flexible Parametric Model ◽  
Typical Shape

Nuptiality is a phenomenon closely related to fertility. The age-specific marriage distribution has a typical shape common in all human populations. In order to estimate this pattern, alternative parametric models have been proposed. However recent evidence suggests that mixture models are required to estimate nuptiality patterns. In this paper, a flexible parametric model is proposed in three versions, appropriate to describe the age pattern of first marriage rates. For evaluation purposes the models as well as the alternative existing models are fitted to a variety of empirical datasets.

Structural-parametric model of an electroelastic actuator for nanomechanics

2020 ◽  
pp. 3-11
Author(s):  
S.M. Afonin
Keyword(s):  
Transfer Function ◽  
Piezoelectric Actuator ◽  
Transfer Functions ◽  
Piezoelectric Effect ◽  
Parametric Model ◽  
Elastic Compliance ◽  
Parametric Models ◽  
Piezo Actuator ◽  
Structural Scheme ◽  
Model Transfer

Structural-parametric models, structural schemes are constructed and the transfer functions of electro-elastic actuators for nanomechanics are determined. The transfer functions of the piezoelectric actuator with the generalized piezoelectric effect are obtained. The changes in the elastic compliance and rigidity of the piezoactuator are determined taking into account the type of control. Keywords electro-elastic actuator, piezo actuator, structural-parametric model, transfer function, parametric structural scheme

Beyond Deep Learning: An Econometric Example

2020 ◽  
Vol 28 (Supp01) ◽  
pp. 31-38 ◽  
Author(s):  
Ruofan Liao ◽  
Paravee Maneejuk ◽  
Songsak Sriboonchitta
Keyword(s):  
Neural Networks ◽  
Deep Learning ◽  
Prediction Models ◽  
Original Data ◽  
Parametric Model ◽  
Parametric Models ◽  
The Past ◽  
Currency Exchange ◽  
Currency Exchange Rate ◽  
Linear And Nonlinear

In the past, in many areas, the best prediction models were linear and nonlinear parametric models. In the last decade, in many application areas, deep learning has shown to lead to more accurate predictions than the parametric models. Deep learning-based predictions are reasonably accurate, but not perfect. How can we achieve better accuracy? To achieve this objective, we propose to combine neural networks with parametric model: namely, to train neural networks not on the original data, but on the differences between the actual data and the predictions of the parametric model. On the example of predicting currency exchange rate, we show that this idea indeed leads to more accurate predictions.

A Non Parametric Model for Magneto Rheological Dampers

1999 ◽  
Author(s):  
Mehdi Ahmadian ◽  
Xubin Song
Keyword(s):  
Test Data ◽  
Mr Damper ◽  
Parametric Model ◽  
Parametric Models ◽  
Magnetic Saturation ◽  
Mr Dampers ◽  
Electro Magnetic ◽  
Magneto Rheological ◽  
Force Characteristics ◽  
Non Parametric

Abstract A non-parametric model for magneto-rheological (MR) dampers is presented. After discussing the merits of parametric and non-parametric models for MR dampers, the test data for a MR damper is used to develop a non-parametric model. The results of the model are compared with the test data to illustrate the accuracy of the model. The comparison shows that the non-parametric model is able to accurately predict the damper force characteristics, including the damper non-linearity and electro-magnetic saturation. It is further shown that the parametric model can be numerically solved more efficiently than the parametric models.

scholarly journals The Parametric Model of the Human Mandible Coronoid Process Created by Method of Anatomical Features

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Nikola Vitković ◽  
Jelena Mitić ◽  
Miodrag Manić ◽  
Miroslav Trajanović ◽  
Karim Husain ◽  
...  
Keyword(s):  
3D Models ◽  
Parametric Model ◽  
Coronoid Process ◽  
Parametric Models ◽  
Specific Patient ◽  
Medical Practitioners ◽  
Anatomical Features ◽  
X Ray ◽  
Human Bones ◽  
Geometrical Data

Geometrically accurate and anatomically correct 3D models of the human bones are of great importance for medical research and practice in orthopedics and surgery. These geometrical models can be created by the use of techniques which can be based on input geometrical data acquired from volumetric methods of scanning (e.g., Computed Tomography (CT)) or on the 2D images (e.g., X-ray). Geometrical models of human bones created in such way can be applied for education of medical practitioners, preoperative planning, etc. In cases when geometrical data about the human bone is incomplete (e.g., fractures), it may be necessary to create its complete geometrical model. The possible solution for this problem is the application of parametric models. The geometry of these models can be changed and adapted to the specific patient based on the values of parameters acquired from medical images (e.g., X-ray). In this paper, Method of Anatomical Features (MAF) which enables creation of geometrically precise and anatomically accurate geometrical models of the human bones is implemented for the creation of the parametric model of the Human Mandible Coronoid Process (HMCP). The obtained results about geometrical accuracy of the model are quite satisfactory, as it is stated by the medical practitioners and confirmed in the literature.

scholarly journals Model Averaging with AIC Weights for Hypothesis Testing of Hormesis at Low Doses

Dose-Response ◽  
2017 ◽  
Vol 15 (2) ◽  
pp. 155932581771531
Author(s):  
Steven B. Kim ◽  
Nathan Sanders
Keyword(s):  
Hypothesis Testing ◽  
Dose Response ◽  
Statistical Power ◽  
Parametric Model ◽  
Semiparametric Models ◽  
Parametric Models ◽  
Large Sample Size ◽  
Low Doses ◽  
P Values ◽  
The Impact

For many dose–response studies, large samples are not available. Particularly, when the outcome of interest is binary rather than continuous, a large sample size is required to provide evidence for hormesis at low doses. In a small or moderate sample, we can gain statistical power by the use of a parametric model. It is an efficient approach when it is correctly specified, but it can be misleading otherwise. This research is motivated by the fact that data points at high experimental doses have too much contribution in the hypothesis testing when a parametric model is misspecified. In dose–response analyses, to account for model uncertainty and to reduce the impact of model misspecification, averaging multiple models have been widely discussed in the literature. In this article, we propose to average semiparametric models when we test for hormesis at low doses. We show the different characteristics of averaging parametric models and averaging semiparametric models by simulation. We apply the proposed method to real data, and we show that P values from averaged semiparametric models are more credible than P values from averaged parametric methods. When the true dose–response relationship does not follow a parametric assumption, the proposed method can be an alternative robust approach.

Optimal Parametric Model for Vortex Tube Using DOE

2011 ◽  
Author(s):  
Basel Alsayyed ◽  
Mohammad O. Hamdan ◽  
Emad Elnajjar
Keyword(s):  
Vortex Tube ◽  
Parametric Model ◽  
Geometric Parameters ◽  
Parametric Models ◽  
Outlet Temperature ◽  
Key Factors ◽  
Response Factors ◽  
Outlet Flow ◽  
Mass Flow Rates ◽  
Heating Load

In this study, a vortex tube geometric parametric model will be developed and the parameters will be considered as factors that affect the performance of a vortex tube. SolidWorks is used to generate parametric models; Minitab is used for Design Of Experiments (DOE) combination setups. A 3D printer is used to produce a physical model of the vortex tube to fit each of the DOE combinations. The study reports the effect of different geometric parameters on the cooling/heating load and the outlet temperature. The geometric parameters are investigated by measuring temperatures, pressures and mass flow rates for the inlet and hot/cold outlet flow. Two key factors were considered, namely mass fraction and angle of nozzle. Response factors analyzed are the maximum hot temperature (THMax) and the minimum cold temperature (TCMin).

scholarly journals Flexible parametric model for survival data subject to dependent censoring

2019 ◽  
Vol 62 (1) ◽  
pp. 136-156 ◽  
Author(s):  
Negera Wakgari Deresa ◽  
Ingrid Van Keilegom
Keyword(s):  
Survival Data ◽  
Parametric Model ◽  
Dependent Censoring ◽  
Flexible Parametric Model ◽  
Data Subject

scholarly journals Using the loess method to describe the effect of temperature on development rate

2017 ◽  
Vol 53 (No. 4) ◽  
pp. 226-231 ◽  
Author(s):  
Liu Junhe ◽  
Yan Yan ◽  
Yu Mingfu ◽  
Parajulee Megha N ◽  
Shi Peijian ◽  
...  
Keyword(s):  
Goodness Of Fit ◽  
Parametric Model ◽  
Development Rate ◽  
Parametric Models ◽  
Effect Of Temperature ◽  
Published Data ◽  
Local Regression ◽  
Temperature Dependent ◽  
Dependent Development ◽  
Development Rates

Temperature has a significant influence on development rates of insects and mites. Many parametric models were built to describe the temperature-dependent development rates. However, these models provided different shapes of the curves of development rate versus temperature. For different datasets, investigators have to spend much time on considering which the parametric model is the best for describing the temperature-dependent development rates. In the present study, we encourage investigators to use an important non-parametric model, the loess method, which belongs to local regression methods. The loesS method is used to fit some published data on the development rate of aphids to check the goodness-of-fit. We find that the loess method is very flexible for fitting the given datasets. Thus, we consider that the loess method can be used to describe the effect of temperature on the development rate of insects or mites.

Identifying High-Value CAD Models: An Exploratory Study on Dimensional Variability As Complexity Indicator

2018 ◽  
Author(s):  
Jorge D. Camba ◽  
Manuel Contero ◽  
Pedro Company ◽  
David Pérez-López ◽  
Jeffrey Otey
Keyword(s):  
Parametric Model ◽  
Parametric Models ◽  
Graph Structure ◽  
Semantic Level ◽  
Digital Product ◽  
Quantitative Metrics ◽  
Reliable Assessment ◽  
Cad Models ◽  
Downstream Processes

Digital product data quality has proven to be a unifying theme in designing and reusing efficient products, particularly in the context of the Model-Based Enterprise (MBE). More specifically, the quality of the master model (usually a history-based parametric model) is critical, as it determines the quality of all secondary models used in subsequent downstream processes. However, no quantitative metrics exist that can provide a reliable assessment of quality at a high semantic level. In this paper, we introduce dimensional variability as a quality indicator for parametric models that connects the effective variability range of the dimensional constraints in a model to the robustness and flexibility of the parametric geometry, which determines its reusability. As a validation effort, we report the results of a study where a set of parametric models of varying complexity was analyzed, and discuss the significance of the links between the proposed metric and various aspects of the internal graph structure of the CAD model.

Optimization Design of Oil-Water Separator Based on Fuzzy Synthetic Evaluation

2014 ◽  
Vol 945-949 ◽  
pp. 231-235
Author(s):  
Yin Dong Zhang ◽  
Yang Liu
Keyword(s):  
Optimization Design ◽  
Parametric Model ◽  
Fluid Simulation ◽  
Parametric Models ◽  
Design Parameters ◽  
Fuzzy Synthetic Evaluation ◽  
Evaluation Indexes ◽  
Water Separator ◽  
Oil Water ◽  
Synthetic Evaluation

The method of Fuzzy Synthetic Evaluation is presented to optimize oil-water separator design in the paper. Firstly, the key design parameters to be optimized are determined. Secondly, the CAD technology is applied to achieve parametric models of separator and the CFD technology is employed to fulfill fluid simulation of separator parametric models. Then, with the evaluation indexes established, the simulation results of each separator parametric model are evaluated by Fuzzy Synthetic Evaluation. Finally, by comparing the evaluation value of every parametric model, the optimal design model of oil-water separator is achieved.

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