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Statistical modelling of roadside and urban background ultrafine and accumulation mode particle number concentrations using generalized additive models

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SCIENCE OF THE TOTAL ENVIRONMENT 2020年第0期703卷 134570-000页

作者： Gerling, Lars Loeschau, Gunter Wiedensohler, Alfred Weber, Stephan Tech Univ Carolo Wilhelmina Braunschweig Inst Geoecol Climatol & Environm Meteorol Langer Kamp 19c D-38106 Braunschweig Germany Saxon State Off Environm Agr & Geol LfULG Pillnitzer Pl 3 D-01326 Dresden Germany Leibniz Inst Tropospher Res TROPOS Permoserstr 15 D-04318 Leipzig Germany

Quantification of the exposure of urban residents to ultrafine particle number concentrations (UFP) is challenging due to its high spatial and temporal variability. Hence, statistical models, e.g. generalized additive models (GAM), may be used to estimate time series or spatial characteristics of UFP. The GAM approach allows the representation of non-linear relations of a response variable with explanatory variables without the need to pre-define model functions. Up to now, GAMs were usually fitted to UFP data from a single site or from mobile measurement campaigns with limited temporal coverage. In this study, GAMs were used to determine UFP, accumulation mode particle (ACC) and total number concentration (TNC) at five urban sites in the cities of Leipzig and Dresden, Germany for the period 2011-2013. As explanatory variables, reanalysis data sets of meteorological quantities, urban geometry and traffic volume data were evaluated. Variables causing concurvity, which is the equivalent to collinearity in nonlinear model approaches, were neglected to guarantee the interpretability of the final models. The models were then validated in a ten-fold cross-validation approach. The final models contained smooth functions for the building surface fraction, planetary boundary layer height, traffic volume, air temperature, wind direction, atmospheric pressure, relative humidity, global radiation and precipitation. Adjusted coefficients of determination (R-adj(2).) for the final models were R-adj(2) = 0.44 for UFP, R-adj(2) = 0.51 for ACC and R-adj(2) = 0.48 for TNC. Coefficients of determination of the cross-validation were in a similar range (0.44 for UFP, 0.51 for ACC, 0.49 for TNC). Finally, our study shows that GAMs are able to represent important processes that contribute to the particle number concentration from the smooth functions, i.e. emission, dilution, nucleation, deposition and long-range transport. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Ultrafine particles Accumulation mode particles Particle number concentration Urban air quality generalized additive model Statistical model

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Estimating test-day milk yields by modeling proportional daily yields: Going beyond linearity

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JOURNAL OF DAIRY SCIENCE 2023年第12期106卷 8979-9005页

作者： Wu, Xiao-Lin Wiggans, George R. Norman, H. Duane Enzenauer, Heather A. Miles, Asha M. Tassell, Curtis P. Van Baldwin IV, Ransom L. Burchard, Javier Durr, Joao Council Dairy Cattle Breeding Bowie MD 20716 USA Univ Wisconsin Madison Dept Anim & Dairy Sci Madison WI 53706 USA USDA Agr Res Serv Anim Genom & Improvement Lab Beltsville MD 20705 USA

In the United States, lactation milk yields are not measured directly but are calculated from the test-day milk yields. Still, test-day milk yields are estimated from partial yields obtained from single milkings. Vari-ous methods have been proposed to estimate test-day milk yields, primarily to deal with unequal milking intervals dating back to the 1970s and 1980s. The Wiggans model is a de facto method for estimating test-day milk yields in the United States, which was initially proposed for cows milked 3 times daily, as-suming a linear relationship between a proportional test-day milk yield and milking interval. However, the linearity assumption did not hold precisely in Holstein cows milked twice daily because of prolonged and uneven milking intervals. The present study reviewed and evaluated the nonlinear models that extended the Wiggans model for estimating daily or test-day milk yields. These nonlinear models, except step functions, demonstrated smaller errors and greater accuracies for estimated test-day milk yields compared with the conventional methods. The nonlinear models offered additional benefits. For example, the locally weighted regression model (e.g., locally estimated scatterplot smoothing) could utilize data information in scalable neighborhoods and weigh observations according to their distance in milking interval time. General additive models provide a flexible, unified framework to model nonlinear predictor variables additively. Another draw-back of the conventional methods is a loss of accuracy caused by discretizing milking interval time into large bins while deriving multiplicative correction factors for estimating test-day milk yields. To overcome this prob-lem, we proposed a general approach that allows milk yield correction factors to be derived for every possible milking interval time, resulting in more accurately estimated test-day milk yields. This approach can be applied to any model, including nonparametric models.

关键词： dairy cattle locally weighted regression generalized additive model milk yields

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Data-driven determination of plant growth stages for improved weather index insurance design

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AGRICULTURAL FINANCE REVIEW 2024年第4/5期84卷 297-319页

作者： Zhou, Jing Odening, Martin Okhrin, Ostap Tech Univ Dresden Friedrich List Fac Transportat Chair Stat & Econometr Dresden Germany Ctr Scalable Data Analyt & Artificial Intelligence Dresden Germany Humboldt Univ Dept Agr Econ Farm Management Grp Berlin Germany

PurposeThis paper aims to improve the delimitation of plant growth stages in the context of weather index insurance design. We propose a data-driven phase division that minimizes estimation errors in the weather-yield relationship and investigate whether it can substitute an expert-based determination of plant growth phases. We combine this procedure with various statistical and machine learning estimation methods and compare their ***/methodology/approachUsing the example of winter barley, we divide the complete growth cycle into four sub-phases based on phenology reports and expert instructions and evaluate all combinations of start and end points of the various growth stages by their estimation errors of the respective yield models. Some of the most commonly used statistical and machine learning methods are employed to model the weather-yield relationship with each selected method we *** results confirm that the fit of crop-yield models can be improved by disaggregation of the vegetation period. Moreover, we find that the data-driven approach leads to similar division points as the expert-based approach. Regarding the statistical model, in terms of yield model prediction accuracy, Support Vector Machine ranks first and Polynomial Regression last;however, the performance across different methods exhibits only minor ***/valueThis research addresses the challenge of separating plant growth stages when phenology information is unavailable. Moreover, it evaluates the performance of statistical and machine learning methods in the context of crop yield prediction. The suggested phase-division in conjunction with advanced statistical methods offers promising avenues for improving weather index insurance design.

关键词： Weather index insurance Temporal basis risk Plant growth stages generalized additive model Machine learning

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Nonlinear connection between remnant cholesterol and stroke risk: evidence from the China health and retirement longitudinal study

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LIPIDS IN HEALTH AND DISEASE 2023年第1期22卷 1-12页

作者： Wang, Yuanqing Zha, Fubing Han, Yong Cai, Ying Chen, Miaoling Yang, Cui Cai, Xiaodong Hu, Haofei Cao, Changchun Luo, Jiao Shenzhen Univ Affiliated Hosp 1 Shenzhen Peoples Hosp 2 Dept Funct Neurol Shenzhen 518035 Guangdong Peoples R China Shenzhen Univ Affiliated Hosp 1 Shenzhen Peoples Hosp 2 Dept Rehabil Shenzhen 518035 Guangdong Peoples R China Shenzhen Univ Affiliated Hosp 1 Shenzhen Peoples Hosp 2 Dept Emergency Shenzhen 518035 Guangdong Peoples R China Shenzhen Dapeng New Dist Nanao Peoples Hosp Dept Rehabil 6 Renmin Rd Shenzhen 518000 Guangdong Peoples R China Shenzhen Univ Affiliated Hosp 1 Shenzhen Peoples Hosp 2 Dept Nephrol 3002 Sungang West Rd Shenzhen 518000 Guangdong Peoples R China

Objective The evidence on the relationship between remnant cholesterol (RC) and stroke remains controversial. Therefore, this study aimed to explore the relationship between RC and stroke risk in a Chinese population of middle-aged and elderly individuals. Methods The present study included 10067 Chinese subjects of middle-aged and elderly individuals. The connection between RC and incident stroke was investigated using the multivariate Cox proportional hazards regression model, several sensitivity analyses, generalized additive models, and smoothed curve fitting. Results A total of 1180 participants with stroke were recorded during the follow-up period. The multivariate Cox proportional hazards regression model identified a positive connection between RC and stroke risk (hazard ratio (HR) = 1.087, 95% confidence interval (CI): 1.001-1.180). In addition, the current study discovered a nonlinear connection between RC and incident stroke, and the point of inflection for RC was 1.78 mmol/L. The risk of stroke increased by 25.1% with each unit increase in RC level when RC was < 1.78 mmol/L (HR:1.251, 95%CI: 1.089-1.437, P = 0.0015). The results were not affected by sensitivity tests. Conclusion The current study showed a positive and nonlinear connection between RC and stroke risk in a middle-aged and elderly Chinese population. These findings provided new information to help researchers better understand the relationship between RC levels and incident stroke.

关键词： Stroke Remnant cholesterol Nonlinear relationship generalized additive model Smoothed curve fitting

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Distribution and geographic differences in stable isotope ratios of diamond squid Thysanoteuthis rhombus (Cephalopoda: Thysanoteuthidae) in Japanese waters

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FISHERIES OCEANOGRAPHY 2023年第3期32卷 255-266页

作者： Ohshimo, Seiji Kodama, Taketoshi Tawa, Atsushi Tanaka, Hiroshige Tanaka, Yosuke Yasuhara, Go Tokuyasu, Michihiro Minami, Yoichi Fisheries Resources Inst Nagasaki Field Stn Nagasaki 8512213 Japan Fisheries Resources Inst Yokohama Field Stn Yokohama 2218529 Japan Shimane Prefectural Fisheries Technol Ctr Hamada 6970051 Japan Tottori Prefectural Fisheries Lab Sakai Minato Tottori 6840046 Japan Okinawa Prefectural Fisheries Oceanog & Technol Ct Itoman 9010354 Japan

Diamond squid Thysanoteuthis rhombus (Troschel, 1857), which can grow to a dorsal mantle length of similar to 100 cm in 1 year, is an important fisheries resource in subtropical and temperate waters worldwide. Around Japan, it is an important resource in the East China Sea, Sea of Japan, and western North Pacific Subtropical Gyre, including the Kuroshio area. It is not known if linkages occur between these habitats. To clarify the species distribution, we estimated the habitat of young squid using a generalized additive model based on trawl surveys and analyzed carbon and nitrogen stable isotope ratios (delta C-13 and delta N-15) in tissue samples. Based on trawl observations, young squid were distributed around northeastern Taiwan and the Okinawa Islands in June-July and in the Sea of Japan and the Kuroshio extension areas in August-September. We observed ontogenetic changes in the stable isotope ratios. The delta N-15 values in large diamond squid (dorsal mantle length > 400 mm) were significantly lower in the Pacific than those in other areas. Considering that the delta N-15 of forage fish is low in the Pacific and high in the East China Sea and Sea of Japan, large diamond squid in the northwest Pacific presumably have two distinct habitats.

关键词： diamond squid generalized additive model habitat stable isotope ratios

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Factors determining nest-site selection of surface-nesting seabirds: a case study on the world's largest pelagic bird, the Wandering Albatross (Diomedea exulans)

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IBIS 2023年第1期165卷 190-203页

作者： Momberg, Mia Ryan, Peter G. Hedding, David W. Schoombie, Janine Goddard, Kyle A. Craig, Ken J. Le Roux, Peter C. Univ Pretoria Dept Plant & Soil Sci Pretoria South Africa Univ Cape Town FitzPatrick Inst African Ornithol Rondebosch South Africa Univ South Africa Dept Geog Pretoria South Africa Univ Pretoria Dept Mech & Aeronaut Engn Pretoria South Africa

Several factors may drive bird nest-site selection, including predation risk, resource availability, weather conditions and interaction with other individuals. Understanding the drivers affecting where birds nest is important for conservation planning, especially where environmental change may alter the distribution of suitable nest-sites. This study investigates which environmental variables affect nest-site selection by the Wandering Albatross Diomedea exulans, the world's largest pelagic bird. Here, wind characteristics are quantitatively investigated as a driver of nest-site selection in surface-nesting birds, in addition to several topographical variables, vegetation and geological characteristics. Nest locations from three different breeding seasons on sub-Antarctic Marion Island were modelled to assess which environmental factors affect nest-site selection. Elevation was the most important determinant of nest-site selection, with Wandering Albatrosses only nesting at low elevations. Distance from the coast and terrain roughness were also important predictors, with nests more generally found close to the coast and in flatter terrain, followed by wind velocity, which showed a hump-shaped relationship with the probability of nest occurrence. Nests occurred more frequently on coastal vegetation types, and were absent from polar desert vegetation (generally above c. 500 m elevation). Of the variables that influence Wandering Albatross nest location, both vegetation type and wind characteristics are likely to be influenced by climate change, and have already changed over the last 50 years. As a result, the availability of suitable nest-sites needs to be considered in light of future climate change, in addition to the impacts that these changes will have on foraging patterns and prey distribution. More broadly, these results provide insights into how a wide range of environmental variables, including wind, can affect nest-site selection of surface-nesting seabirds.

关键词： generalized additive model generalized linear model topography vegetation type wind

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Age-Dependent Association Between Body Mass Index and All-Cause Mortality Among Patients with Hypertension: A Longitudinal Population-Based Cohort Study in China

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CLINICAL EPIDEMIOLOGY 2023年 15卷 1159-1170页

作者： Huang, Yifang Peng, Jiahuan Wang, Weibing Zheng, Xueying Qin, Guoyou Xu, Huilin Fudan Univ Shanghai Inst Infect Dis & Biosecur Shanghai Peoples R China Fudan Univ Sch Publ Hlth Dept Biostat Natl Hlth CommissKey Lab Hlth Technol Assessment Shanghai Peoples R China Shanghai Minhang Ctr Dis Control & Prevent Shanghai Peoples R China Fudan Univ Sch Publ Hlth Dept Biostat Natl Hlth CommissKey Lab Hlth Technol Assessment 138 Yi Xue Yuan Rd Shanghai 200032 Peoples R China Shanghai Minhang Ctr Dis Control & Prevent 965 Zhong Yi Rd Shanghai 201101 Peoples R China

Purpose: The association between body mass index (BMI) and all-cause mortality may vary among hypertensive patients of different ages. This study aimed to investigate the age-dependent association between BMI and all-cause mortality among patients with *** and Methods: A total of 212,394 participants with hypertension aged 20- 85 years from Minhang Hypertension Standardization Management System in Shanghai of China were included. Follow-up began at the time when individuals were first recorded and ended at death, loss to follow-up, or December 31, 2018, whichever came first. additive Cox proportional hazards models with thin plate smoothing functions and conventional Cox proportional hazards models were adopted to examine the relationship between BMI, age, and mortality. The joint effect of BMI and age on mortality was assessed using a bivariate response ***: We found that the BMI-mortality relationship followed a U-shaped pattern, with a trough at 26- 27 kg/m(2). Compared with normal weight, underweight was associated with a 50% increased risk of premature mortality (hazard ratio 1.50, 95% confidence interval 1.43 to 1.57). Whereas among those aged 45- 59 and 60- 85 years, overweight was associated with 13% (0.87, 0.80 to 0.94) and 18% (0.82, 0.80 to 0.84) reduction in risk of death, respectively. Bivariate response model indicated a significant interaction between BMI and age (P < 0.05). Among younger and older patients, we found a descending trend for mortality risk, with BMI increasing at different age levels, whereas a reverse J-shaped relation pattern was observed among middle-aged ***: The impact of BMI on all-cause mortality in hypertensive patients varies with age, and moderate weight gain may benefit longevity in middle-aged and older patients.

关键词： body mass index age all-cause mortality hypertension generalized additive model

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Accurate and Computational Efficient Estimation with Non-Linear Statistical models 6

Accurate and Computational Efficient Estimation with Non-Lin...

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Conference on Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications VI

作者： Chen, Maximillian G. Allen, Ryan A. Ramac-Thomas, Liane C. Strait, Melissa E. Johns Hopkins Univ Appl Phys Lab 11100 Johns Hopkins Rd Laurel MD 20723 USA

ISBN: (纸本)9781510674219;9781510674202

With the current growing availability of datasets coming from multiple sources and domains, systems onboard our military assets have an immediate need of being functional in multiple domains, handling large amounts of data, and implementing fast and appropriate analyses for these datasets. However, onboard systems often have very limited computational resources upon which to process these tasks. generalized additive models (GAMs), which are statistical model that are better able to account for non-linear relationships between independent and dependent variables, have been shown in multiple application areas to yield more accurate estimates than models that only assume linear relationships. GAMs require fitting smooth functions of independent variables, and potentially interactions between two or more independent variables with tensor products, commonly using penalized basis splines (P-splines). However, when trying to make predictions for previously unseen feature vectors and without the benefit of significant computing power and necessary software packages, computing the necessary P-spline basis values in order to make predictions becomes computationally intractable. We show that approximating the smooth functions of a trained GAM with cubic splines yields very good estimates that result in minimal loss of accurate compared to the original trained GAM model while significantly decreasing computational cost. These two benefits have resulted in our method being adopted by a primary contractor handling high-fidelity analyses. We will show our implementation results on simulated and real datasets, discuss our findings, and conclude with remarks on future work.

关键词： generalized additive model statistical estimation computational cost spline methods

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The price of clean air - quantifying air pollution exposure in real estate decisions

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JOURNAL OF PROPERTY INVESTMENT & FINANCE 2024年第2期42卷 166-189页

作者： Restle, Rebecca Cajias, Marcelo Knoppik, Anna PATRIZIA SE Investment Strategy & Res Augsburg Germany Univ Regensburg IREBS Regensburg Germany

PurposeThe purpose of this paper is to explore the significance impact of air quality as a contributing factor on residential property rents by applying geo-informatics to economic issues. Since air pollution poses a severe health threat, city residents should have a right to know about the (invisible) hazards they are exposed ***/methodology/approachWithin spatial-temporal modeling of air pollutants in Berlin, Germany, three interpolation techniques are tested. The most suitable one is selected to create seasonal maps for 2018 and 2021 with pollution concentrations for particulate matter values and nitrogen dioxide for each 1,000 m2 cell within the administrative boundaries. Based on the evaluated pollution particulate matter values, which are used as additional variables for semi-parametric regressions the impact of the air quality on rents is *** findings reveal a compelling association between air quality and the economic aspect of the residential real estate market, with noteworthy implications for both tenants and property investors. The relationship between air pollution variables and rents is statistically significant. However, there is only a "willingness-to- pay" for low particulate matter values, but not for nitrogen dioxide concentrations. With good air quality, residents in Berlin are willing to pay a higher rent (3%).Practical implicationsThese results suggest that a "marginal willingness-to-pay" occurs in a German city. The research underscores the multifaceted impact of air quality on the residential rental market in Berlin. The evidence supports the notion that a cleaner environment not only benefits human health and the planet but also contributes significantly to the economic bottom line of property ***/valueThe paper has a unique data engineering approach. It collects spatiotemporal data from network of state-certified measuring sites to create an index of air pollution. This spatial information is merged

关键词： Residential real estate Air pollution Particulate matter concentrations Empirical Bayesian Kriging Rents generalized additive model Machine learning

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An investigation into the forces shaping the evolution of global shipping alliances

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MARITIME POLICY & MANAGEMENT 2024年第7期51卷 1295-1314页

作者： Ju, Huizhu Zeng, Qingcheng Haralambides, Hercules Li, Yimeng Dalian Maritime Univ Sch Maritime Econ & Management Dalian Peoples R China Univ Paris 01 Sorbonne Sch Econ Pantheon Sorbonne Paris France Erasmus Univ Econometr Inst Erasmus Sch Econ Rotterdam Netherlands

Global shipping alliances have become an important institution in international seaborne trade. Their raison d'etre is higher efficiency and lower costs, to the benefit of the consumer. However, experiences from GSA operations during the COVID-19 supply chain crisis show that GSAs may have considerable market power, not quite aligned with the spirit of the lawmaker who has exempted them from antitrust laws. This raises many questions this paper attempts to answer: What drives the formation, stability and dissolution of GSAs? And have external and internal factors, such as government policies, ship sizes and freight rates, had always the same effect on GSAs over time? We decompose industry concentration (HHI) into seven components. This is done based on the Variational Mode Decomposition model. The components are subsequently reconstructed through gray correlation. Next, a generalized additive model is specified, to analyze the relationships between influencing factors and the evolution of GSAs. We look both at the development (trend) of industry concentration, as well as its fluctuations (cyclicality) over time. We show that effects vary over time, with the same factors having different impacts on GSAs at different times. The paper can assist policymakers in their efforts to regulate and supervise container shipping.

关键词： Global shipping alliances evolution influencing factors Variational Mode Decomposition generalized additive model

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