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Introduction of the GAM model for regional low-flow frequency analysis at ungauged basins and comparison with commonly used approaches

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ENVIRONMENTAL MODELLING & SOFTWARE 2018年 109卷 256-271页

作者： Ouarda, T. B. M. J. Charron, C. Hundecha, Y. St-Hilaire, A. Chebana, F. INRS ETE Canada Res Chair Stat Hydroclimatol 490 Couronne Quebec City PQ G1K 9A9 Canada Swedish Meteorol & Hydrol Inst Norrkoping Sweden

generalized additive models (GAMs) are introduced in this study for the regional estimation of low-flow characteristics at ungauged basins and compared to other approaches commonly used for this purpose. GAMs provide more flexibility in the shape of the relationships between the response and explanatory variables in comparison to classical models such as multiple linear regression (MLR). Homogeneous regions are defined here using the methods of hierarchical cluster analysis, canonical correlation analysis and region of influence. GAMs and MLR are then used within the delineated regions and also for the whole study area. In addition, a spatial interpolation method is also tested. The different models are applied for the regional estimation of summer and winter low-flow quantiles at stations in Quebec, Canada. Results show that for a given regional delineation method, GAMs provide improved performances compared to MLR.

关键词： Low flows Regional estimation Canonical correlation analysis Region of influence Hierarchical cluster analysis generalized additive models

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Advocating better habitat use and selection models in bird ecology

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REVISTA BRASILEIRA DE ORNITOLOGIA 2018年第2期26卷 90-104页

作者： Xavier Palacio, Facundo Fac Ciencias Nat & Museo Div Zool Vertebrados Secc Ornitol Paseo Bosque S-NB1900FWA La Plata Buenos Aires Argentina Consejo Nacl Invest Cient & Tecn Paseo Bosque S-NB1900FWA La Plata Buenos Aires Argentina

Studies on habitat use and habitat selection represent a basic aspect of bird ecology, due to its importance in natural history, distribution, response to environmental changes, management and conservation. Basically, a statistical model that identifies environmental variables linked to a species presence is searched for. In this sense, there is a wide array of analytical methods that identify important explanatory variables within a model, with higher explanatory and predictive power than classical regression approaches. However, some of these powerful models are not widespread in ornithological studies, partly because of their complex theory, and in some cases, difficulties on their implementation and interpretation. Here, I describe generalized linear models and other five statistical models for the analysis of bird habitat use and selection outperforming classical approaches: generalized additive models, mixed effects models, occupancy models, binomial N-mixture models and decision trees (classification and regression trees, bagging, random forests and boosting). Each of these models has its benefits and drawbacks, but major advantages include dealing with non-normal distributions (presence-absence and abundance data typically found in habitat use and selection studies), heterogeneous variances, non-linear and complex relationships among variables, lack of statistical independence and imperfect detection. To aid ornithologists in making use of the methods described, a readable description of each method is provided, as well as a flowchart along with some recommendations to help them decide the most appropriate analysis. The use of these models in ornithological studies is encouraged, given their huge potential as statistical tools in bird ecology.

关键词： binomial mixture models classification trees generalized additive models generalized linear models mixed models occupancy models regression trees

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Unravelling the Predictive Power of Telematics Data in Car Insurance Pricing

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JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS 2018年第5期67卷 1275-1304页

作者： Verbelen, Roel Antonio, Katrien Claeskens, Gerda Katholieke Univ Leuven Belgium Netherlands Univ Amsterdam Belgium Netherlands Katholieke Univ Leuven ORSTAT Naamrestr 69 3000 Leuven B-3555 Leuven Belgium

A data set from a Belgian telematics product aimed at young drivers is used to identify how car insurance premiums can be designed based on the telematics data collected by a black box installed in the vehicle. In traditional pricing models for car insurance, the premium depends on self-reported rating variables (e.g. age and postal code) which capture characteristics of the policy(holder) and the insured vehicle and are often only indirectly related to the accident risk. Using telematics technology enables tailor-made car insurance pricing based on the driving behaviour of the policyholder. We develop a statistical modelling approach using generalized additive models and compositional predictors to quantify and interpret the effect of telematics variables on the expected claim frequency. We find that such variables increase the predictive power and render the use of gender as a rating variable redundant.

关键词： Compositional predictors generalized additive models Pay as you drive insurance Risk classification Structural 0s Usage-based insurance

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Predictive distribution models of European hake in the south-central Mediterranean Sea

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HYDROBIOLOGIA 2018年第1期821卷 153-172页

作者： Garofalo, G. Fezzani, S. Gargano, F. Milisenda, G. Ben Abdallah, O. Hamida, N. Ben Hadj Jarboui, O. Chemmam-Abdelkader, B. Khoufi, W. Micallef, R. Mifsud, R. Gancitano, S. Rizzo, P. Zgozi, S. Ceriola, L. Arneri, E. Fiorentino, F. CNR Ist Ambiente Marino Costiero Mazara Del Vallo TP Italy Inst Natl Sci & Technol Mer Ctr La Goulette La Goulette Tunisia Univ Palermo Dept Energy Informat Engn & Math Models DEIM Palermo Italy Inst Natl Sci & Technol Mer Ctr Sfax Sfax Tunisia MSDEC Dept Fisheries & Aquaculture Fisheries Resource Unit Marsa Malta MBRC Tajura Libya FAO MedSudMed Dept Fisheries & Aquaculture Rome Italy

The effective management and conservation of fishery resources requires knowledge of their spatial distribution and notably of their critical life history stages. Predictive modelling of the European hake (Merluccius merluccius L., 1758) distribution was developed in the south-central Mediterranean Sea by means of historical fisheries-independent databases available in the region. The study area included the international waters of the south-central Mediterranean Sea and the territorial waters of Italy, Malta, Tunisia and Libya. Distribution maps of predicted population abundance index, and probabilistic occurrence of recruits and large adults were obtained by means of generalized additive models using depth and seafloor characteristics as predictors. Presence/absence data of the two life stages was obtained using threshold values applied to the mean weight of the survey catches. Modelling results largely matched previously reported knowledge on habitat preference of the species and its critical life phases. Hake recruits showed an occurrence peak at 200 m depth with preference for soft bottoms. Large adults preferred deeper and harder bottom substrates. Prediction maps allowed to improve our knowledge on the distributional patterns of one of the most important shared stocks in the south-central Mediterranean. This knowledge is essential for an appropriate development of regional-spatial-based management plans.

关键词： Species distribution modelling Merluccius merluccius generalized additive models Recruits habitat Large adults habitat Seafloor geophysical features Strait of Sicily

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Distribution and abundance patterns of three coexisting species of Patella (Mollusca Gastropoda) in the intertidal areas of the NW Iberian Peninsula: Implications for management

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FISHERIES RESEARCH 2018年 198卷 86-98页

作者： Casal, Gema Acena-Matarranz, Sara Fernandez-Marquez, Diana Fernandez, Nuria Maynooth Univ Natl Ctr Geocomputat 2nd Floor Iontas BldgNorth Campus Maynooth Kildare Ireland Univ A Coruna Fac Ciencias Campus A Coruna La Coruna 15071 Spain Xefatura Terr A Coruna Consellerta Do Mar Xunta De Galici Spain

Using a combination of geostatistical methods and generalized additive models (GAMs), we have analyzed the combined effect of spatial, environmental and biological factors on the density of Patella vulgata, Patella depressa and Patella ulyssiponensis, three limpet species coexisting in rocky intertidal areas of the Galician coast (NW Iberian Peninsula). The best multivariate GAM fit to the data explained, on average, 54% of the observed variation in density of these species, revealing the influence of spatial (latitude and longitude) and environmental factors (temperature). The influence of biological factors such as reproductive status and density of the species, as well as those of coexisting species, was also detected. The results suggest the existence of spatial and temporal segregation behaviours to decrease intra- and interspecific competition. They confirm P. vulgata as a migratory species and reveal P. depressa also as a migrant limpet, while P. ulyssiponensis belongs to the non-migratory group. Geostatistical analysis showed that P. depressa is the dominant species in areas more exposed to wave action, whilst P. vulgata dominates sheltered area. In addition, the three limpet species are spatially structured in patches, whose density and size vary according to the type of coast (Atlantic/Cantabrian) and to the degree of wave exposure. These results reveal the importance of carrying out assessments at the local level and in those areas particularly vulnerable to exploitation, such as sheltered areas, where densities and recruitment are lower. This information can be useful for decision-making aimed at the management of this resource, as well as for the efficient distribution of effort with respect to geographical fishing areas.

关键词： Patella spp. Spatial distribution Geostatistics generalized additive models Management Sustainability

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Regional-scale surface temperature variability allows prediction of Pacific bluefin tuna recruitment

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ICES JOURNAL OF MARINE SCIENCE 2018年第4期75卷 1341-1352页

作者： Muhling, Barbara A. Tommasi, Desiree Ohshimo, Seiji Alexander, Michael A. DiNardo, Gerard Univ Calif Santa Cruz CIMEC La Jolla CA 92037 USA NOAA Southwest Fisheries Sci Ctr Natl Marine Fisheries Serv La Jolla CA 92037 USA Natl Res Inst Far Seas Fisheries Japan Fisheries Res & Educ Agcy Shimizu Ku 5-7-1 Orido Shizuoka 4248633 Japan NOAA Earth Syst Res Lab Boulder CO 80305 USA

Future sustainable management of fisheries will require resilience to the effects of environmental variability and climate change on stock productivity. In this study, we examined relationships between sea surface temperature(SST)in the region between Taiwan and the Sea of Japan, and annual recruitment of Pacific bluefin tuna (Thunnus orientalis: PBF) over the past 35 years. Spatial correlation maps showed that warmer SSTs south of Shikoku, in the East China Sea and in the Sea of Japan from summer to late fall were associated with above average recruitment. SST anomalies near larval and juvenile habitats were most strongly correlated with local air temperatures generalized additive models predicting annual PBF recruitment from SST fields suggested that the influence of SST on recruitment was stronger than that of spawning stock biomass. Correlations between SST and recruitment likely reflect biological processes relevant to early juvenile habitat suitability. The influence of late fall SSTs could also be a result of varying availability of age-0 fish to the troll fishery;however, the relative importance of these processes was not clear. Despite these knowledge gaps, the strong predictive power of SST on PBF recruitment can allow more proactive management of this species under varying environmental conditions.

关键词： fisheries oceanography generalized additive models Pacific bluefin tuna

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Automatic specification of piecewise linear additive models: application to forecasting natural gas demand

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STATISTICS AND COMPUTING 2018年第1期28卷 201-217页

作者： Gascon, Alberto Sanchez-Ubeda, Eugenio F. Comillas Pontif Univ Inst Res Technol IIT Tech Sch Engn ICAI Santa Cruz de Marcenado 26 Madrid 28015 Spain

When facing any forecasting problem not only is accuracy on the predictions sought. Also, useful information about the underlying physics of the process and about the relevance of the forecasting variables is very much appreciated. In this paper, it is presented an automatic specification procedure for models that are based on additivity assumptions and piecewise linear regression. This procedure allows the analyst to gain insight about the problem by examining the automatically selected model, thus easily checking the validity of the forecast. Monte Carlo simulations have been run to ensure that the model selection procedure behaves correctly under weakly dependent data. Moreover, comparison over other well-known methodologies has been done to evaluate its accuracy performance, both in simulated data and in the context of short-term natural gas demand forecasting. Empirical results show that the accuracy of the proposed model is competitive against more complex methods such as neural networks.

关键词： generalized additive models Prediction Natural gas demand Short-term forecasting Piecewise linear models Nonlinear modeling

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Spatio-temporal dynamics and behavioural ecology of a "demersal" fish population as detected using research survey pelagic trawl catches: the Eastern Baltic Sea cod (Gadus morhua) (vol 76, pg 1591, 2019)

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ICES JOURNAL OF MARINE SCIENCE 2019年第6期76卷 1931-1931页

作者： Casini, Michele Tian, Huidong Hansson, Martin Grygiel, Wlodzimierz Strods, Guntars Statkus, Romas Sepp, Elor Groehsler, Tomas Orio, Alessandro Larson, Niklas Swedish Univ Agr Sci Inst Marine Res Dept Aquat Resources Lysekil Sweden Swedish Meteorol & Hydrol Inst Gothenburg Sweden Natl Marine Fisheries Res Inst Dept Fisheries Resources Gdynia Poland Inst Food Safety Anim Hlth & Environm Dept Fish Resources Res Riga Latvia Minist Agr Fisheries Serv Klaipeda Lithuania Univ Tartu Estonian Marine Inst Tallinn Estonia Thunen Inst Balt Sea Fisheries Rostock Germany

Cod is usually monitored for scientific purposes using bottom trawl surveys, although its regular pelagic occurrence is well documented. Here we analysed, using generalized additive models, the spatio-temporal changes in the Eastern Baltic cod adult population using pelagic catches from an acoustic survey covering 37 years and the whole central Baltic Sea. Our analysis shows that in the northern areas cod catch per unit effort (CPUE, kg h-1) was high in the early 1980s whereas it dropped and remained very low thereafter. Conversely, in the southernmost area CPUE largely oscillated after the early 1990s. Our model was able to capture key ecological features of the Baltic cod such as preferred depth of occurrence and response to hypoxic conditions. The model also revealed a clear daily cycle of CPUEs, indicating diel vertical migrations at the population level. The temporal trends of pelagic CPUEs generally followed those from the bottom trawl surveys, although differences were observed especially in the recent years with a relative decline in the cod occurring in the pelagic waters. Our results point to the great potential of acoustic survey trawl catches to complement bottom trawl surveys for investigating the spatio-temporal population dynamics and behaviour of the Baltic cod.

关键词： acoustic survey behavioural ecology demersal species generalized additive models pelagic occurrence spatial and temporal dynamics

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Moderate fire severity is best for the diversity of most of the pollinator guilds in Mediterranean pine forests

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ECOLOGY 2019年第3期100卷 e02615-e02615页

作者： Lazarina, Maria Devalez, Jelle Neokosmidis, Lazaros Sgardelis, Stefanos P. Kallimanis, Athanasios S. Tscheulin, Thomas Tsalkatis, Panagiotis Kourtidou, Marina Mizerakis, Vangelis Nakas, Georgios Palaiologou, Palaiologos Kalabokidis, Konstantinos Vujic, Ante Petanidou, Theodora Univ Aegean Dept Geog Lab Biogeog & Ecol Mitilini 81100 Greece Aristotle Univ Thessaloniki Sch Biol Dept Ecol Thessaloniki 54124 Greece Univ Aegean Dept Geog Mitilini 8110 Greece Univ Novi Sad Dept Biol & Ecol Trg Dositeja Obradovica 2 YU-21000 Novi Sad Serbia

Fire, a frequent disturbance in the Mediterranean, affects pollinator communities. We explored the response of major pollinator guilds to fire severity, across a fire-severity gradient at different spatial scales. We show that the abundance of all pollinator groups responded to fire severity, and that bees and beetles showed in addition a significant species-diversity response. Bees, sawflies, and wasps responded to fire severity at relatively small spatial scales (250-300 m), whereas flies and beetles responded at larger spatial scales. The response of bees, sawflies, and wasps was unimodal, as predicted by the intermediate disturbance hypothesis, whereas flies and beetles showed a negative response. A possible explanation is that the observed patterns (spatial scale and type of response) are driven by taxa-specific ecological and life-history traits, such as nesting preference and body size, as well as the availability of resources in the postfire landscape. Our observational study provides an insight into the effect of fire severity on pollinators. However, future research exploring the explicit link between the pre- and postfire landscape structure and pollinator traits and responses is required for further establishment and understanding of cause-effect relationships.

关键词： abundance bee flies bees beetles diversity fire severity generalized additive models hoverflies intermediate disturbance hypothesis sawflies wasps

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Housing price prediction: parametric versus semi-parametric spatial hedonic models (vol 20, pg 27, 2017)

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JOURNAL OF GEOGRAPHICAL SYSTEMS 2018年第1期20卷 107-109页

作者： Montero, Jose-Maria Minguez, Roman Fernandez-Aviles, Gema Univ Castilla La Mancha Fac Law & Social Sci Dept Stat Toledo 45071 Spain Univ Castilla La Mancha Dept Stat Fac Social Sci Cuenca 16071 Spain

House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction.

关键词： generalized additive models Housing prices Mixed models Penalized splines Semi-parametric spatial hedonic models

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