Efficient discriminating design for a class of nested polynomial regression models

Metrika ◽  
2011 ◽  
Vol 75 (6) ◽  
pp. 809-817
Author(s):  
Min-Hsiao Tsai
Keyword(s):  
Regression Models ◽  
Polynomial Regression ◽  
Polynomial Regression Models

Effect of enzymatic hydrolysis on the production of free amino acids from boarfish (Capros aper) using second order polynomial regression models

LWT ◽  
2016 ◽  
Vol 68 ◽  
pp. 470-476 ◽  
Author(s):  
K. Shikha Ojha ◽  
Carlos Alvarez ◽  
Prabhash Kumar ◽  
Colm P. O'Donnell ◽  
Brijesh K. Tiwari
Keyword(s):  
Amino Acids ◽  
Enzymatic Hydrolysis ◽  
Free Amino Acids ◽  
Free Amino ◽  
Regression Models ◽  
Polynomial Regression ◽  
Second Order ◽  
Order Polynomial ◽  
Polynomial Regression Models

Growth relationships of individual flowers during late stages of floral development of Rhododendron L. 'Prize' and 'Gloria'

1998 ◽  
Vol 76 (8) ◽  
pp. 1350-1358
Author(s):  
H Brent Pemberton ◽  
Harold F Wilkins ◽  
James S Hodges
Keyword(s):  
Regression Models ◽  
Polynomial Regression ◽  
Cold Treatment ◽  
Female Flower ◽  
Growth Patterns ◽  
Strongly Correlated ◽  
Floral Part ◽  
Growth Measurement ◽  
Hormonal Content ◽  
Polynomial Regression Models

Single terminal inflorescences from two-stemmed plants of Rhododendron L. cv. 'Prize' and 'Gloria' were recurrently sampled during a 9°C cold treatment and subsequent forcing period in an 18°C growth chamber until plants reached anthesis. At each sample period, bud length and width were measured on each inflorescence, while subtending bud scale, petal, stamen ('Gloria' only), style, peduncle and ovary length, ovary width, and flower weight were determined on the two most basally attached flowers within an inflorescence for each cultivar. Polynomial regression models were calculated for each floral growth measurement over time, except for bud length and width, for each of the four flowers within a cultivar. Comparison of regression models revealed differences in floral part growth patterns among the various flowers within each cultivar. During the first week of placement in 18°C forcing temperatures after the cold treatment, bud length was the only floral part to grow on 'Prize' plants, while only female flower parts grew on 'Gloria' plants. These results indicate differences in growth resumption patterns between cultivars after cold storage. However, petal and style length were strongly correlated to flower weight for both cultivars indicating that these measurements could be used in laboratory or field situations to determine the floral stage of growth. The growth equations described would be useful for controlling the variability among shoots and flowers for analytical determinations, such as hormonal content analysis, and for studying relationships of floral growth patterns to environmental stimuli that could be used to control flowering. The statistical techniques used in this research make it possible to reduce the number of plants for such studies, as measurements taken on different flowers on the same plant can be used for floral part growth comparisons despite the inherent correlation present between such measurements.Key words: morphology, dormancy, growth modeling, multivariate multiple regression, controlled environment.

scholarly journals EVOLUTION OF MORTALITY FOR COLORECTAL CANCER IN BRAZIL AND REGIONS, BY SEX, 1996-2015

2018 ◽  
Vol 55 (1) ◽  
pp. 61-65 ◽  
Author(s):  
Viviane Gomes Parreira DUTRA ◽  
Virgilio Augusto Gomes PARREIRA ◽  
Raphael Mendonça GUIMARÃES
Keyword(s):  
Colorectal Cancer ◽  
Regression Models ◽  
Polynomial Regression ◽  
Public Health Problem ◽  
Mortality Rates ◽  
Early Interventions ◽  
Polynomial Regression Models ◽  
And Behavior ◽  
Priority Populations ◽  
Colorectal Cancer Mortality

ABSTRACT BACKGROUND: Colorectal cancer is among the three most frequent neoplasms in Brazil, being a public health problem. OBJECTIVE: To describe distribution pattern of colorectal cancer mortality in Brazil and regions, according to sex, between 1996 and 2015. METHODS: Values of standardized and stratified mortality rates by sex between 1996 and 2015 were used, through polynomial regression models and joinpoint analysis. RESULTS: It was observed that, for linear trends in mortality rates, for both sexes, there is a statistically significant trend increasing in both models, with rates and trends, and higher for men than for women, respectively, 7.3% per year (R2=0.95, P<0.001) and 6.5% per year (R2=0.87, P<0.001). It is observed a difference in magnitude and behavior of trend between the regions. CONCLUSION: It is understood that it is important to know the trend of rates in order to define priority populations for early interventions that increase survival and reduce mortality.

scholarly journals Trends in mortality due to breast cancer among women in the state of Rio de Janeiro, Brazil, 1996-2011

2015 ◽  
Vol 20 (3) ◽  
pp. 895-903
Author(s):  
Daniele Bittencourt Ferreira ◽  
Inês Echenique Mattos
Keyword(s):  
Breast Cancer ◽  
Rio De Janeiro ◽  
Regression Models ◽  
Polynomial Regression ◽  
Population Group ◽  
Mortality Rates ◽  
The State ◽  
Data Source ◽  
Polynomial Regression Models ◽  
Series Study

A descriptive time series study was conducted in order to analyze the mortality rates for breast cancer in two age brackets (< 60 years and ≥ 60 years), in areas of the state of Rio de Janeiro (inland, metropolitan area, capital and state). The data source was the Mortality Information System. Mortality rates were analyzed for four-year periods, between 1996 and 2011, and the ratios between the incidences for the two age brackets in each area. The trend in annual mortality rates was analyzed with the Joinpoint program and polynomial regression models. The ratios between the incidences observed were 7-8 times higher in women aged 60 years or older. Joinpoint analyses indicated a linear decline in mortality rates in the state and the capital for the whole population and for women aged 60 and over in the same areas. The polynomial regression models allowed the observation of periods of increasing and decreasing rates and a tendency to stabilization at the end of the period. Despite the declining trend, the magnitude of mortality from breast cancer is still high among women aged 60 and older, and it is important to investigate associated factors in this population group.

scholarly journals Lack-of-fit Testing for Polynomial Regression Models Without Replications

2019 ◽  
Vol 8 (5) ◽  
pp. 49
Author(s):  
Maha A. Omair ◽  
Abdullah A. Al-Shiha ◽  
Ruba A. Alyafi
Keyword(s):  
Regression Models ◽  
Polynomial Regression ◽  
Error Component ◽  
Constant Variance ◽  
Lack Of Fit ◽  
Fit Testing ◽  
Independent Variable ◽  
Continuous Covariate ◽  
Simulation Results ◽  
Polynomial Regression Models

Parametric and non-parametric approaches are developed to test the adequacy of the polynomial model Y=&beta;&deg;+j=1p&beta;jXj+&epsilon; &nbsp;when there is no replication in the values of the independent variable. The proposed tests avoid partitioning of the sample space of the continuous covariate. This paper suggests three tests based on the following concept: if the model is appropriate for a selected application, then the error component &epsilon;1,&epsilon;2,&hellip;,&epsilon;n is a random sample with zero mean and constant variance. Simulation results are provided to illustrate the power and size of the proposed tests. An example is used to illustrate the methodologies. These tests are also compared with the classical lack-of-fit test to demonstrate their advantage.

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