Prediction of throughfall quantities under different forest stands

1982 ◽  
Vol 12 (3) ◽  
pp. 474-481 ◽  
Author(s):  
M. K. Mahendrappa ◽  
D. G. O. Kingston
Keyword(s):  
Regression Models ◽  
Balsam Fir ◽  
Simple Linear Regression ◽  
Linear Regression Models ◽  
Quantitative Distribution ◽  
Rain Gauges ◽  
Case Application ◽  
The Difference ◽  
And Control ◽  
The Relationship

The quantitative distribution of throughfall in fertilizer-treated and control plots under six softwood and three hardwood stands and rainfall in open areas close to these stands were intensively measured during 1977–1978. Standard rain gauges and improvised funnel-type collectors were used for measuring both throughfall and rainfall in the open. The improvised funnel-type collectors with an orifice smaller than that of the standard rain gauges were found to be suitable for accurately measuring quantities of both open rainfall and throughfall. Simple linear regression models of the form Y = b − a were sufficient to predict throughfall quantities (Y) based on rainfall (X) measurements. The relationship between the quantities of throughfall and rainfall was highly significant in each case. Application of urea at a rate of 225 kg N ha−1 did not affect either the slope (b) or the elevation (a) of the relationship. No significant differences were found between the relationships calculated for 1977 and 1978 for any species except balsam fir (Abiesbalsamea (L.) Mill) and larch (Lurixlaricina (Du Roi) K. Koch). The difference for balsam fir was probably a result of extensive defoliation by the spruce budworm (Choristoneurafumiferana (Clem.)). In most cases, values of the slopes (b) of the models for the different species were not significantly different. The nine species did, however, differ significantly from one another in terms of the minimum quantity of rain (a/b) that must fall before throughfall was measurable in the collectors.

Relationship Between Mental Health, Resilience, and Physical Activity in Older Adults: A 2-Year Longitudinal Study

2021 ◽  
pp. 1-9
Author(s):  
Maria Priscila Wermelinger Ávila ◽  
Jimilly Caputo Corrêa ◽  
Alessandra Lamas Granero Lucchetti ◽  
Giancarlo Lucchetti
Keyword(s):  
Mental Health ◽  
Physical Activity ◽  
Older Adults ◽  
Regression Models ◽  
Linear Regression Models ◽  
Physically Active ◽  
Effective Interventions ◽  
Self Sufficiency ◽  
The Relationship

The aim of this study was to longitudinally investigate the association between resilience and mental health in older adults and to determine the influence of physical activity on this relationship. A total of 291 older adults were included in a 2-year follow-up study. Adjusted linear regression models evaluated the association between resilience at baseline and mental health after 2 years in sufficiently and insufficiently physically active older adults. A negative correlation was found between resilience at baseline and depression, anxiety, and stress after 2 years for the overall sample. This association changed after stratifying the group. Sufficiently physically active individuals made greater use of the resilience components “Self-Sufficiency” and “Perseverance,” whereas insufficiently physically active individuals made greater use of “Meaning of Life” and “Existential Singularity.” Physical activity can influence the relationship between resilience and mental health. These results can help guide the devising of more effective interventions for this age group.

scholarly journals The Relationship Between Alcohol Beverage Types and Violence

2018 ◽  
Vol 49 (1) ◽  
pp. 183-200
Author(s):  
Aleksandra J. Snowden
Keyword(s):  
Regression Models ◽  
Neighborhood Characteristics ◽  
Substantial Evidence ◽  
Alcohol Outlets ◽  
Observation Instrument ◽  
Beverage Type ◽  
Social Observation ◽  
Ecological Association ◽  
The Difference ◽  
The Relationship

There is substantial evidence of an ecological association between off-premise alcohol outlets and violence. We know less, however, about how specific beverage types that are sold in the outlets might explain the difference in violence rates across different alcohol outlets. Data on alcohol beverage types were collected for all off-premise alcohol outlets in Milwaukee, Wisconsin, using a systematic social observation instrument. Spatially lagged regression models were estimated to determine whether the variation in alcohol beverage types is related to robbery density net of important neighborhood predictors of crime rates. Availability of all alcohol beverage types (beer, wine, spirits, premixed, single beer, single spirits, single premixed) was positively associated with the density of robberies, net of neighborhood characteristics. Reducing alcohol beverages, regardless of the beverage type, sold at off-premise alcohol outlets may reduce violence in communities.

scholarly journals Concentration of Banking Sector and Loan Markups in Short Term: An Example from Poland

2014 ◽  
Vol 5 (2) ◽  
pp. 26-44
Author(s):  
Krysztof Drachal
Keyword(s):  
Monetary Policy ◽  
Banking Sector ◽  
Mortgage Market ◽  
Future Research ◽  
Simple Linear Regression ◽  
Short Term ◽  
Monthly Data ◽  
Regression Techniques ◽  
The Difference ◽  
The Relationship

The aim of this paper is to present an analysis of the relationship between concentration of the banking sector and banks' markups on offered loans. The markup is understood as the difference between the rate offered by banks and the reference rate fixed by the Monetary Policy Council. The period between 2009 and 2013 was analyzed. Monthly data from the Polish banking sector were considered. This paper also consists of the literature review, which focuses on the mortgage market. The methodology used for the analysis is based mainly on simple linear regression techniques. It is found that such methods are not sufficient to give conclusive answers. Therefore additional future research is proposed.

scholarly journals Effects of Winter Snow Cover on Spring Soil Moisture Based on Remote Sensing Data Product over Farmland in Northeast China

2020 ◽  
Vol 12 (17) ◽  
pp. 2716
Author(s):  
Shuang Liang ◽  
Xiaofeng Li ◽  
Xingming Zheng ◽  
Tao Jiang ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Linear Regression ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regression Models ◽  
Linear Regression Models ◽  
Winter Snow ◽  
The Relationship

Spring soil moisture (SM) is of great importance for monitoring agricultural drought and waterlogging in farmland areas. While winter snow cover has an important impact on spring SM, relatively little research has examined the correlation between winter snow cover and spring SM in great detail. To understand the effects of snow cover on SM over farmland, the relationship between winter snow cover parameters (maximum snow depth (MSD) and average snow depth (ASD)) and spring SM in Northeast China was examined based on 30 year passive microwave snow depth (SD) and SM remote-sensing products. Linear regression models based on winter snow cover were established to predict spring SM. Moreover, 4 year SD and SM data were applied to validate the performance of the linear regression models. Additionally, the effects of meteorological factors on spring SM also were analyzed using multiparameter linear regression models. Finally, as a specific application, the best-performing model was used to predict the probability of spring drought and waterlogging in farmland in Northeast China. Our results illustrated the positive effects of winter snow cover on spring SM. The average correlation coefficient (R) of winter snow cover and spring SM was above 0.5 (significant at a 95% confidence level) over farmland. The performance of the relationship between snow cover and SM in April was better than that in May. Compared to the multiparameter linear regression models in terms of fitting coefficient, MSD can be used as an important snow parameter to predict spring drought and waterlogging probability in April. Specifically, if the relative SM threshold is 50% when spring drought occurs in April, the prediction probability of the linear regression model concerning snow cover and spring SM can reach 74%. This study improved our understanding of the effects of winter snow cover on spring SM and will be beneficial for further studies on the prediction of spring drought.

scholarly journals Association between Cross-Cultural Social Adaptation and Overseas Life Satisfaction among Chinese Medical Aid Team Members (CMATMs) in Africa

2019 ◽  
Vol 16 (9) ◽  
pp. 1572 ◽  
Author(s):  
Xiaochang Chen ◽  
Xiaojun Liu ◽  
Wei Yu ◽  
Anran Tan ◽  
Chang Fu ◽  
...  
Keyword(s):  
Life Satisfaction ◽  
Regression Models ◽  
Cross Cultural ◽  
Social Adaptation ◽  
Linear Regression Models ◽  
Team Members ◽  
Medical Aid ◽  
Electronic Questionnaires ◽  
The Relationship ◽  
Overall Life Satisfaction

This study evaluated the relationship between cross-cultural social adaptation and overseas life satisfaction among Chinese medical aid team members (CMATMs) in Africa. A revised Chinese version of the Sociocultural Adaptation Scale (CSCAS) was used to measure participants’ cross-cultural social adaptation. The self-designed survey of the CMATMs’ overseas life satisfaction includes the following five aspects: food, housing, transportation, entertainment, and security. Electronic questionnaires were distributed non-randomly. Linear regression models were established to explore the association between cross-cultural social adaptation and all dimensions of overseas life satisfaction. After adjusting all the confounders, compared with moderate adaptation, poor adaptation was negatively correlated with all dimensions of overseas life satisfaction (B for food = −0.71, B for housing = −0.76, B for transportation = −0.70, B for entertainment = −0.53, B for security = −0.81, B for overall satisfaction = −0.71, all p < 0.001), whereas good adaptation was positively associated with all dimensions of overseas life satisfaction (B for food = 1.23, B for housing = 1.00, B for transportation = 0.84, B for entertainment = 0.84, B for security = 0.76, B for overall life satisfaction = 0.94, all p < 0.001). This study shows that a better cross-cultural social adaptation was positively connected to a higher level of overseas life satisfaction in general, and more specifically to higher levels of satisfaction with food, housing, transportation, entertainment, and security. This knowledge can be utilized in promoting cross-cultural social adaptation and overseas life satisfaction among CMATMs in Africa.

BAYESIAN IDENTIFICATION OF OUTLIERS AND CHANGE-POINTS IN MEASUREMENT ERROR MODELS

2005 ◽  
Vol 08 (04) ◽  
pp. 433-449 ◽  
Author(s):  
FERNANDO A. QUINTANA ◽  
PILAR L. IGLESIAS ◽  
HELENO BOLFARINE
Keyword(s):  
Linear Regression ◽  
Outlier Detection ◽  
Change Point ◽  
Regression Models ◽  
Point Problem ◽  
Linear Regression Models ◽  
Outlier Identification ◽  
Change Point Problem ◽  
Error In Variables ◽  
The Relationship

The problem of outlier and change-point identification has received considerable attention in traditional linear regression models from both, classical and Bayesian standpoints. In contrast, for the case of regression models with measurement errors, also known as error-in-variables models, the corresponding literature is scarce and largely focused on classical solutions for the normal case. The main object of this paper is to propose clustering algorithms for outlier detection and change-point identification in scale mixture of error-in-variables models. We propose an approach based on product partition models (PPMs) which allows one to study clustering for the models under consideration. This includes the change-point problem and outlier detection as special cases. The outlier identification problem is approached by adapting the algorithms developed by Quintana and Iglesias [32] for simple linear regression models. A special algorithm is developed for the change-point problem which can be applied in a more general setup. The methods are illustrated with two applications: (i) outlier identification in a problem involving the relationship between two methods for measuring serum kanamycin in blood samples from babies, and (ii) change-point identification in the relationship between the monthly dollar volume of sales on the Boston Stock Exchange and the combined monthly dollar volumes for the New York and American Stock Exchanges.

Amendment of traditional assessment measures for the negative symptoms of schizophrenia

2018 ◽  
Vol 49 ◽  
pp. 50-55 ◽  
Author(s):  
Aida Farreny ◽  
Judith Usall ◽  
Jorge Cuevas-Esteban ◽  
Susana Ochoa ◽  
Gildas Brébion
Keyword(s):  
Verbal Memory ◽  
Regression Models ◽  
Negative Symptoms ◽  
Linear Regression Models ◽  
Illness Duration ◽  
Traditional Assessment ◽  
Syndrome Scale ◽  
Assessment Measures ◽  
Negative Syndrome ◽  
The Relationship

AbstractSchizophrenia research based on traditional assessment measures for negative symptoms appears to be, to some extent, unreliable. The limitations of the Positive and Negative Syndrome Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS) have been extensively acknowledged and should be taken into account. The aim of this study is to show how the PANSS and the SANS conflate negative symptoms and cognition and to offer alternatives for the limitations found.MethodsA sample of 117 participants with schizophrenia from two independent studies was retrospectively investigated. Linear regression models were computed to explore the effect of negative symptoms and illness duration as predictors of cognitive performance.ResultsFor the PANSS, the item “abstract thinking” accounted for the association between negative symptoms and cognition. For the SANS, the “attention” subscale predicted the performance in verbal memory, but illness duration emerged as a stronger predictor than negative symptoms for outcomes of processing speed, verbal and working memory.ConclusionUtilizing alternative models to the traditional PANSS and SANS formats, and accounting for illness duration, provide more precise evidence on the relationship between negative symptoms and cognition. Since these measures are still extensively utilized, we recommend adopting more rigorous approaches to avoid misleading results.

On Consistency of Estimators in Simple Linear Regression Models

2002 ◽  
Vol 53 (3-4) ◽  
pp. 261-264 ◽  
Author(s):  
Anindya Roy ◽  
Thomas I. Seidman
Keyword(s):  
Linear Regression ◽  
Least Squares ◽  
Regression Models ◽  
Sufficient Condition ◽  
Simple Linear Regression ◽  
Linear Regression Models ◽  
Least Squares Estimators

We derive a property of real sequences which can be used to provide a natural sufficient condition for the consistency of the least squares estimators of slope and intercept for a simple linear regression models.

Sign in / Sign up

Export Citation Format

Share Document