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Predicting vulnerability through hybrid modeling combining GAM and XGBoost - A case of affected population vulnerability to tropical cyclone in Hainan Province

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INTERNATIONAL JOURNAL OF DISASTER RISK REDUCTION 2024年 111卷

作者： Meng, Chenna Xu, Wei Qiao, Yu Qin, Lianjie Su, Peng Liao, Xinli Beijing Normal Univ Minist Educ Key Lab Environm Change & Nat Disaster Beijing 100875 Peoples R China Beijing Normal Univ State Key Lab Earth Surface Proc & Resource Ecol Beijing 100875 Peoples R China Minist Emergency Management Acad Disaster Reduct & Emergency Management Beijing 100875 Peoples R China Minist Educ Beijing 100875 Peoples R China Beijing Normal Univ Fac Geog Sci Beijing Peoples R China Tsinghua Univ Sch Safety Sci Beijing 100084 Peoples R China

Tropical cyclones are one of the most destructive natural disasters, frequently occurring in the southeastern coastal areas of China, causing huge losses. Accurate characterization and prediction of negative impacts are necessary to minimize impact on coastal cities. However, a complex interaction between hazard intensity and other drivers is involved in the impact of some extreme tropical cyclones, which are often worthy of attention. In this study, a quantitative vulnerability assessment model of tropical cyclones considering the mutual relation between hazard intensity and environmental drivers was developed using the generalized additive model (GAM), random forest (RF), and extreme gradient boosting (XGBoost) for the case of Hainan Province, China. In the testing dataset, the root mean squared error of the optimal model was 0.1393, and the mean absolute percentage error of the optimal model was 35.2 % for spikes in the affected population rate. The spikes in the affected population rate were predicted well by the hybrid model jointly considering nonlinear multivariable regression models and undersampling machine learning methods.

关键词： Multiple hazards Tropical cyclones generalized additive models Random forest Extreme gradient boosting China

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Variance Propagation for Density Surface models

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JOURNAL OF AGRICULTURAL BIOLOGICAL AND ENVIRONMENTAL STATISTICS 2021年第2期26卷 306-323页

作者： Bravington, Mark V. Miller, David L. Hedley, Sharon L. Commonwealth Sci & Ind Res Org Marine Lab Hobart Tas Australia Univ St Andrews Ctr Res Ecol & Environm Modelling St Andrews Fife Scotland Univ St Andrews Sch Math & Stat St Andrews Fife Scotland

Spatially explicit estimates of population density, together with appropriate estimates of uncertainty, are required in many management contexts. Density surface models (DSMs) are a two-stage approach for estimating spatially varying density from distance sampling data. First, detection probabilities-perhaps depending on covariates-are estimated based on details of individual encounters;next, local densities are estimated using a GAM, by fitting local encounter rates to location and/or spatially varying covariates while allowing for the estimated detectabilities. One criticism of DSMs has been that uncertainty from the two stages is not usually propagated correctly into the final variance estimates. We show how to reformulate a DSM so that the uncertainty in detection probability from the distance sampling stage (regardless of its complexity) is captured as an extra random effect in the GAM stage. In effect, we refit an approximation to the detection function model at the same time as fitting the spatial model. This allows straightforward computation of the overall variance via exactly the same software already needed to fit the GAM. A further extension allows for spatial variation in group size, which can be an important covariate for detectability as well as directly affecting abundance. We illustrate these models using point transect survey data of Island Scrub-Jays on Santa Cruz Island, CA, and harbour porpoise from the SCANS-II line transect survey of European waters. Supplementary materials accompanying this paper appear on-line.

关键词： Abundance estimation Distance sampling generalized additive models Line transect sampling Point transect sampling Spatial modelling

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Climate sensitivity of understory trees differs from overstory trees in temperate mesic forests

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ECOLOGY 2021年第3期102卷 e03264-e03264页

作者： Rollinson, Christine R. Alexander, M. Ross Dye, Alex W. Moore, David J. P. Pederson, Neil Trouet, Valerie Ctr Tree Sci Morton Arboretum Lisle IL 60532 USA Midwest Dendro LLC Naperville IL 60565 USA Oregon State Univ Dept Forest Ecosyst & Soc Corvallis OR 97333 USA Univ Arizona Sch Nat Resources & Environm Tucson AZ 85721 USA Harvard Univ Petersham MA 01366 USA Univ Arizona Lab Tree Ring Res Tucson AZ 85721 USA

The response of understory trees to climate variability is key to understanding current and future forest dynamics. However, analyses of climatic effects on tree growth have primarily focused on the upper canopy, leaving understory dynamics unresolved. We analyzed differences in climate sensitivity based on canopy position of four common tree species (Acer rubrum, Fagus grandifolia, Quercus rubra, and Tsuga canadensis) using growth information from 1,084 trees across eight sites in the northeastern United States. Effects of canopy position on climate response varied, but were significant and often nonlinear, for all four species. Compared to overstory trees, understory trees showed stronger reductions in growth at high temperatures and varied shifts in precipitation response. This contradicts the prevailing assumption that climate responses, particularly to temperature, of understory trees are buffered by the overstory. Forest growth trajectories are uncertain in compositionally and structurally complex forests, and future demography and regeneration dynamics may be misinferred if not all canopy levels are represented in future forecasts.

关键词： canopy position climate-growth relationship forest structure generalized additive models tree rings

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A Person- and Time-Varying Vector Autoregressive Model to Capture Interactive Infant-Mother Head Movement Dynamics

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MULTIVARIATE BEHAVIORAL RESEARCH 2021年第5期56卷 739-767页

作者： Chen, Meng Chow, Sy-Miin Hammal, Zakia Messinger, Daniel S. Cohn, Jeffrey F. Penn State Univ Human Dev & Family Studies 420 Biobehav Hlth BldgUniv Pk State Coll PA 16802 USA Carnegie Mellon Univ Inst Robot Pittsburgh PA 15213 USA Univ Miami Dept Psychol Coral Gables FL 33124 USA Univ Miami Dept Pediat Coral Gables FL 33124 USA Univ Miami Dept Mus Engn Coral Gables FL 33124 USA Univ Miami Dept Elect Coral Gables FL 33124 USA Univ Miami Dept Comp Engn Coral Gables FL 33124 USA Univ Pittsburgh Dept Psychol Pittsburgh PA 15260 USA Univ Pittsburgh Dept Psychiat Pittsburgh PA 15260 USA Univ Pittsburgh Dept Intelligent Syst Pittsburgh PA 15260 USA

Head movement is an important but often overlooked component of emotion and social interaction. Examination of regularity and differences in head movements of infant-mother dyads over time and across dyads can shed light on whether and how mothers and infants alter their dynamics over the course of an interaction to adapt to each others. One way to study these emergent differences in dynamics is to allow parameters that govern the patterns of interactions to change over time, and according to person- and dyad-specific characteristics. Using two estimation approaches to implement variations of a vector-autoregressive model with time-varying coefficients, we investigated the dynamics of automatically-tracked head movements in mothers and infants during the Face-Face/Still-Face Procedure (SFP) with 24 infant-mother dyads. The first approach requires specification of a confirmatory model for the time-varying parameters as part of a state-space model, whereas the second approach handles the time-varying parameters in a semi-parametric ("mostly" model-free) fashion within a generalized additive modeling framework. Results suggested that infant-mother head movement dynamics varied in time both within and across episodes of the SFP, and varied based on infants' subsequently-assessed attachment security. Code for implementing the time-varying vector-autoregressive model using two R packages,dynrandmgcv, is provided.

关键词： Time-varying parameters vector autoregressive models state-space models generalized additive models parent-infant interactions head movements still-face paradigm

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A general semiparametric Bayesian discrete-time recurrent events model

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BIOSTATISTICS 2021年第2期22卷 266-282页

作者： King, Adam J. Weiss, Robert E. Calif State Polytech Univ Pomona Dept Math & Stat 3801 West Temple Ave Pomona CA 91768 USA Univ Calif Los Angeles Fielding Sch Publ Hlth Dept Biostat 650 Charles E Young Dr South Los Angeles CA 90095 USA

Event time variables are often recorded in a discrete fashion, especially in the case of patient-reported outcomes. This work is motivated by a study of illicit drug users, in which time to drug use cessation has been recorded as a number of whole months. Existing approaches for handling such discrete data include treating the survival times as continuous (with adjustments for inevitable tied outcomes), or using discrete models that omit important features like random effects. We provide a general Bayesian discrete-time proportional hazards model, incorporating a number of features popular in continuous-time models such as competing risks and frailties. Our model also provides flexible baseline hazards for time effects, as well as generalized additive models style semiparametric incorporation of other time-varying covariates. Our specific modeling choices enable efficient Markov chain Monte Carlo inference algorithms, which we provide to the user in the form of a freely available R package called brea. We demonstrate that our model performs better on our motivating substance abuse application than existing approaches. We also present a reproducible application of the brea software to a freely available data set from a clinical trial of anesthesia administration methods.

关键词： Competing risks Cox model Discrete time generalized additive models Recurrent events Semiparametric models Software Substance abuse

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Long-term automatic trap data reveal factors affecting diurnal flight patterns of the Mediterranean Fruit fly

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JOURNAL OF APPLIED ENTOMOLOGY 2021年第5期145卷 427-439页

作者： Goldshtein, Eitan Gazit, Yoav Hetzroni, Amots Timar, Doron Rosenfeld, Lavi Grinshpon, Yossef Cohen, Yafit Agr Res Org ARO Inst Agr Engn Volcani Ctr POB 15159 IL-7505101 Rishon Leziyyon Israel Israel Cohen Inst Biol Control Plants Prod & Mkt Board Yehud Monosson Israel

Mediterranean Fruit Fly (medfly), Ceratitis capitata (Wiedemann), is considered to be one of the most destructive fruit insect pests throughout the world. In recent years, the temporal dynamics of the medfly have been extensively studied by season, and, to a lesser extent, on a daily basis. We exploited, for the first time, a sequential automatic medfly male trapping system, in combination with climate data, to characterize diel flight patterns of male medflies trapped. The process was carried out in four commercial citrus fields over three growing seasons. Results showed that throughout the year, medfly flight activity began 4-6 hr after sunrise and peaked up to 2 to 3 hr before sunset. generalized additive models (GAM) of the 934 days sampled revealed that in the fall, the diurnal flight activity was unimodal, that is, it began increasing at noon, peaking in the afternoon. By contrast, in the spring and summer, the diurnal flight activity exhibited a bimodal pattern, decreasing at midday. GAMs also revealed that hour after sunrise and temperature influenced medfly captures, with the former the more dominant factor. Thus, photophase significantly impacted the medfly's diurnal flight activity in each season. This study demonstrated that automatic traps that timestamp each capture are a primary research tool in insect flight activity studies that contributes to understanding diurnal insect activity within the growing season.

关键词： big data Ceratitis capitata data science generalized additive models insect behaviour pest control

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Robust multipe imputation with GAM

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STATISTICS AND COMPUTING 2024年第4期34卷 121-121页

作者： Templ, Matthias Univ Appl Sci & Arts Northwestern Switzerland Inst Competitiveness & Commun Riggenbachstr 16 CH-4600 Olten Switzerland

Multiple imputation of missing values is a key step in data analytics and a standard process in data science. Nonlinear imputation methods come into play whenever the linear relationship between a response and predictors cannot be linearized by transformations of variables, adding interactions, or using, e.g., quadratic terms. generalized additive models (GAM) and its extension, GAMLSS-where each parameter of the distribution, such as mean, variance, skewness, and kurtosis, can be represented as a function of predictors, are widely used nonlinear methods. However, non-robust methods such as standard GAM's and GAMLSS's can be swayed by outliers, leading to outlier-driven imputations. This can apply concerning both representative outliers-those true yet unusual values of your population-and non-representative outliers, which are mere measurement errors. Robust (imputation) methods effectively manage outliers and exhibit resistance to their influence, providing a more reliable approach to dealing with missing data. The innovative solution of the proposed new imputation algorithm tackles three major challenges related to robustness. (1) A robust bootstrap method is employed to handle model uncertainty during the imputation of a random sample. (2) The approach incorporates robust fitting techniques to enhance accuracy. (3) It effectively considers imputation uncertainty in a resilient manner. Furthermore, any complex model for any variable with missingness can be considered and run through the algorithm. For the real-world data sets used and the simulation study conducted, the novel algorithm imputeRobust which includes robust methods for imputation with GAM's demonstrates superior performance compared to existing imputation methods using GAMLSS. Limitations pertain to the imputation of categorical variables using robust techniques.

关键词： Missing values Multiple imputation generalized additive models Robust estimation Robust bootstrap

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Environmental factors affecting the distribution of deep-water rose shrimp (Parapenaeus longirostris, Lucas, 1846 ) abundance in the Strait of Sicily (Mediterranean Sea)

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CONTINENTAL SHELF RESEARCH 2024年 282卷

作者： Bignami, Francesco Fiorentino, Fabio Garofalo, Germana Zambianchi, Enrico Colella, Simone Sorgente, Roberto Olita, Antonio Landolfi, Angela Quattrocchi, Federico Miller, Peter I. CNR ISMAR SS Roma Via Fosso Cavaliere 100 I-00133 Rome Italy CNR IRBIM SS Mazara Vallo Via L Vaccara 61 I-91026 Mazara Del Vallo TP Italy Univ Napoli Parthenope Naples Italy CoNISMa Naples Italy CNR IAS SS Oristano I-09170 Oristano OR Italy Univ Cagliari CNR ISAC Cagliari Dipartimento Fis Str Pro le MonserratoSestu Km 0 700 I-09042 Cagliari CA Italy Plymouth Marine Lab Remote Sensing Grp Prospect Pl Plymouth PL1 3DH England SZN Stn Zool Anton Dohrn SZN Lungomare Cristoforo Colombo 4521 I-90149 Palermo Italy Univ Palermo Dept Earth & Marine Sci DiSTeM I-90123 Palermo Italy Natl Biodivers Future Ctr Palermo Italy

The distribution of deep-water rose shrimp (Parapenaeus longirostris, FAO 3 alpha code DPS), the main target species of demersal fisheries in the Strait of Sicily, is investigated in relation to surface parameters and biogeochemical processes. Such processes are known to influence sea bottom habitats and may be particularly relevant to the Strait of Sicily because of its relative shallowness and high surface primary production. Shrimp abundances recorded during multi-annual and seasonal trawl surveys (2004-2008) are analyzed. A GAMM and GAM model analysis is performed comparing juvenile abundances to monthly mean spatial patterns of remotely-sensed sea surface temperature (SST) and surface chlorophyll (chl), as well as their frontal structures, with a time-lag of one month, given the pelagic behavior of DPS early life stages preceding settlement. Juvenile and total shrimp abundances are also compared to the flux of particulate organic carbon (POC) to the seabed. The POC flux is computed via 1-D and 3-D models simulating sinking, re-mineralization and horizontal advection and diffusion of surface POC. The latter is derived from surface primary production maps obtained from ocean color data. Results show that the abundance of the juvenile fraction of DPS is significantly correlated with depth, distance to SST fronts and the intensity of chl fronts (correlation R-2 = 80%). Furthermore, results strongly suggest the significant role of bottom POC flux in conditioning the distribution of DPS abundance, indicating that ecological processes occurring in surface waters influence food availability near the seabed in the investigated area.

关键词： Deep-water rose shrimp SST Chlorophyll Fronts POC generalized additive models

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Social behavior in ASD males: The interplay between cognitive flexibility, working memory, and functional connectivity deviations

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DEVELOPMENTAL COGNITIVE NEUROSCIENCE 2025年 71卷 101483页

作者： Chan, Shi Yu Chuah, Jasmine Si Min Huang, Pei Tan, Ai Peng ASTAR Inst Human Dev & Potential IHDP 30 Med Dr Singapore 117609 Singapore Natl Univ Singapore NUS Yong Loo Lin Sch Med 10 Med Dr Singapore 117597 Singapore Natl Univ Hlth Syst Dept Diagnost Imaging 1E Kent Ridge Rd Singapore 119228 Singapore

Autism spectrum disorder (ASD) is highly heterogeneous in presentation. While abnormalities in brain functional connectivity are consistently observed in autistic males, the neurobiological basis underlying the different domains of autism symptoms is unclear. In this study, we evaluated whether individual variations in functional connectivity deviations map to social behavior in ASD males. Using neuroimaging data from the Autism Brain Imaging Data Exchange (ABIDE), we modeled normative trajectories of between-network resting-state functional connectivity (rsFC) in non-ASD males across childhood (n = 321). These normative charts were then applied to ASD males (n = 418) to calculate individual deviation scores (z-scores) that reflect the degree of rsFC atypicality. Deviations in rsFC patterns among the default mode network (DMN), ventral attention network (VAN), frontoparietal network (FPN), and somatomotor network (SMN) were associated with distinct dimensions of social behavior. Cognitive flexibility and working memory mediated the association between VANxDMN z-scores and social behavioral problems. Our findings underscore the potential of normative models to identify atypical brain connectivity at an individual level, revealing the neurobiological patterns associated with social behavioral problems in ASD that are critical for precision diagnosis and intervention. Social outcomes in ASD males may be improved by targeting cognitive flexibility and working memory.

关键词： Autism spectrum disorders Functional connectivity generalized additive models Normative Trajectories Social behavior Executive functioning

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Body mass changes of dabbling and diving ducks wintering in California

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JOURNAL OF WILDLIFE MANAGEMENT 2024年第8期88卷

作者： Herzog, Mark P. Ackerman, Joshua T. Kohl, Jeffrey D. Fettig, Brady L. Hartman, C. Alex Peterson, Sarah H. Casazza, Michael L. Fleskes, Joseph P. US Geol Survey Western Ecol Res Ctr Dixon Field Stn 800 Business Pk DrSuite D Dixon CA 95620 USA

Bird body mass is often used as an index of body condition and fluctuates throughout the year in response to environmental conditions and avian life-history events. We examined the body mass of 59,572 ducks representing 13 species (7 dabbling duck species and 6 diving duck species) harvested within the 3 regions of the Central Valley in California, USA (Sacramento Valley, Suisun Marsh, San Joaquin Valley). Data collection occurred in winter during 5 hunting seasons (2014-2015, 2015-2016, 2017-2018, 2018-2019, 2019-2020). For all species, age, and sex classes, the body mass of dabbling ducks varied temporally and was lowest at the end of the hunting season in late January, declining from the beginning of the hunting season in mid-October (northern pintail [Anas acuta]: -11.4% to -20.4%;northern shoveler [Spatula clypeata]: -3.5% to -17.3%;cinnamon teal [Anas cyanoptera]: -5.0% to -17.1%;American wigeon [Mareca americana]: -6.9% to -12.2%;American green-winged teal [Anas carolinensis]: -5.9% to -11.9%;mallard [Anas platyrhynchos]: -1.8% to -9.6%;gadwall [Mareca strepera]: -2.2% to -8.4%). As expected, adults (after hatch-year) were heavier than immature (hatch-year) birds (within males: 0.6-8.6%;within females: 0.1-6.6%) and males were heavier than females (within adults: 3.1-38.6%;within immatures: 5.4-33.5%) at the end of the hunting season in all species. Within dabbling duck species, body masses did not differ among regions at the beginning of the hunting season but were heavier in the Sacramento Valley (0.5-14.4%) than other areas by the end of the hunting season. In contrast, body masses of diving ducks did not vary substantially during the hunting season or among regions. Diving ducks demonstrated inconsistent changes in mass from the beginning to the end of the season (lesser scaup [Aythya affinis]: 3.4% to 12.3%;canvasback [Aythya valisineria]: 5.1% to 6.1%;bufflehead [Bucephala albeola]: -3.2% to 1.6%;ring-necked duck [Aythya collaris]: -4.9% to 2.6%;common

关键词： Anas spp Aythya spp body condition generalized additive models wintering waterfowl

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