Cited by 13,852Statistical Methods and InferenceStatistical Methods and ApplicationsStatistical Methods and Bayesian Inference

The DOI matches its Crossref record.

Generalized Additive Models: An Introduction with R

Wood, Simon N.·2017·Chapman & Hall/CRC eBooks

DOI 10.1201/9781315370279

Open this paper in CoChat — free account

Abstract

The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before presenting a balanced treatment of the theory and applications of GAMs and related models. The author bases his approach on a framework of penalized regression splines, and while firmly focused on the practical aspects of GAMs, discussions include fairly full explanations of the theory underlying the methods. Use of R software helps explain the theory and illustrates the practical application of the methodology. Each chapter contains an extensive set of exercises, with solutions in an appendix or in the book’s R data package gamair, to enable use as a course text or for self-study.

Integrity signals

Registry

Crossref · 10.1201/9781315370279

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Sorted by citations

Items 901–1,000 of 1,064

Long-term effects of supplementary feeding of moose on browsing impact at a landscape scale
Mathisen, K. M., Milner, J. M., van Beest, F. M., & Skarpe, C. (2013) · Forest Ecology and Management · doi:10.1016/j.foreco.2013.11.037 · Cited by 41
Large medusae in surface waters of the Northern California Current: variability in relation to environmental conditions
Suchman, C. L., Brodeur, R. D., Daly, E. A., & Emmett, R. L. (2012) · Hydrobiologia · doi:10.1007/s10750-012-1055-7 · Cited by 41
Standardized catch and survival rates, and effect of a ban on shark retention, Palau pelagic longline fishery
Gilman, E. L., Chaloupka, M. Y., Merrifield, M., Malsol, N. D., & Cook, C. (2015) · Aquatic Conservation Marine and Freshwater Ecosystems · doi:10.1002/aqc.2599 · Cited by 42
How to build a biodiverse city: environmental determinants of bird diversity within and among 1581 cities
Callaghan, C. T., Poore, A. G. B., Major, R. E., Cornwell, W. K., Wilshire, J. H., & Lyons, M. (2020) · Biodiversity and Conservation · doi:10.1007/s10531-020-02088-1 · Cited by 41
Host specificity and species colouration mediate the regional decline of nocturnal moths in central European forests
Roth, N., Hacker, H. H., Heidrich, L., Frieß, N., García‐Barros, E., Habel, J. C., Thorn, S., & Müller, J. C. (2021) · Ecography · doi:10.1111/ecog.05522 · Cited by 39
Cross-Ecosystem Linkages: Transfer of Polyunsaturated Fatty Acids From Streams to Riparian Spiders via Emergent Insects
Kowarik, C., Martin-Creuzburg, D., & Robinson, C. (2021) · Frontiers in Ecology and Evolution · doi:10.3389/fevo.2021.707570 · Cited by 36
Fast model‐based ordination with copulas
Popovic, G. C., Hui, F. K. C., & Warton, D. I. (2021) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.13733 · Cited by 36
Expansion and evolution of the R programming language
Staples, T. (2022) · Royal Society Open Science · doi:10.1098/rsos.221550 · Cited by 36
Top-predator recovery abates geomorphic decline of a coastal ecosystem
Hughes, B. B., Beheshti, K. M., Tinker, M. T., Angelini, C., Endris, C., Murai, L. Y., Anderson, S. C., Espinosa, S., Staedler, M. M., Tomoleoni, J. A., et al. (2024) · Nature · doi:10.1038/s41586-023-06959-9 · Cited by 42
Different transmission patterns in the early stages of the influenza A(H1N1)v pandemic: A comparative analysis of 12 European countries
Flasche, S., Hens, N., Boëlle, P., Mossong, J., van Ballegooijen, W. M., Nunes, B., Rizzo, C., Popovici, F., Santa-Olalla, P., Hrubá, F., et al. (2011) · Epidemics · doi:10.1016/j.epidem.2011.03.005 · Cited by 39
Prevalence and genetic diversity of Salmonella spp. in a river in a tropical environment in Mexico
Jiménez‐Edeza, M., Martínez-Urtaza, J., Rodríguez‐Álvarez, M. X., León‐Félix, J., & Cháidez, C. (2014) · Journal of Water and Health · doi:10.2166/wh.2014.051 · Cited by 40
The development of understanding through writing
Baaijen, V. M. (2012) · University of Groningen research database (University of Groningen / Centre for Information Technology) · Cited by 40
Accuracy and performance of low‐feature GPS collars deployed on bison Bison bison and caribou Rangifer tarandus
Jung, T. S., Hegel, T. M., Bentzen, T. W., et al. (2018) · Wildlife Biology · doi:10.2981/wlb.00404 · Cited by 39
Examining the diurnal temperature range enigma: why is human health related to the daily change in temperature?
Davis, R. E. L., Hondula, D. M., & Sharif, H. (2019) · International Journal of Biometeorology · doi:10.1007/s00484-019-01825-8 · Cited by 39
Diel patterns in swimming behavior of a vertically migrating deepwater shark, the bluntnose sixgill (Hexanchus griseus)
Coffey, D. M., Royer, M. A., Meyer, C. G., & Holland, K. N. (2020) · PLoS ONE · doi:10.1371/journal.pone.0228253 · Cited by 40
Selenium-associated DNA methylation modifications in placenta and neurobehavioral development of newborns: An epigenome-wide study of two U.S. birth cohorts
Tian, F., Everson, T. M., Lester, B. M., Punshon, T., Jackson, B. P., Hao, K., Lesseur, C., Chen, J., Karagas, M. R., & Marsit, C. J. (2020) · Environment International · doi:10.1016/j.envint.2020.105508 · Cited by 41
References for Ultrasound Staging of Breast Maturation, Tanner Breast Staging, Pubic Hair, and Menarche in Norwegian Girls
Bruserud, I. S., Roelants, M., Oehme, N. H. B., Madsen, A., Eide, G. E., Bjerknes, R., Rosendahl, K., & Júlíusson, P. B. (2020) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgaa107 · Cited by 42
Urban environments and objectively-assessed physical activity and sedentary time in older Belgian and Chinese community dwellers: potential pathways of influence and the moderating role of physical function
Cerin, E., Dyck, D. V., Zhang, C. J. P., Cauwenberg, J. V., Lai, P., & Barnett, A. H. (2020) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-020-00979-8 · Cited by 40
Ocean Acidification Has Impacted Coral Growth on the Great Barrier Reef
Guo, W., Bokade, R., Cohen, A. L., et al. (2020) · Geophysical Research Letters · doi:10.1029/2019gl086761 · Cited by 39
North American Breeding Bird Survey status and trend estimates to inform a wide range of conservation needs, using a flexible Bayesian hierarchical generalized additive model
Smith, A. C., & Edwards, B. P. M. (2020) · Ornithological Applications · doi:10.1093/ornithapp/duaa065 · Cited by 41
Direct and indirect effects of heatwaves on a coral reef fishery
Brown, C. J., Mellin, C., Edgar, G. J., Campbell, M. D., & Stuart‐Smith, R. D. (2020) · Global Change Biology · doi:10.1111/gcb.15472 · Cited by 42
Development of attention networks from childhood to young adulthood: A study of performance, intraindividual variability and cortical thickness
Bøen, R., Ferschmann, L., Vijayakumar, N., Øverbye, K., Fjell, A. M., Espeseth, T., & Tamnes, C. K. (2021) · Cortex · doi:10.1016/j.cortex.2021.01.018 · Cited by 41
Evaluating tree-to-tree competition during stand development in a relict Scots pine forest: how much does climate matter?
Marqués, L., Camarero, J. J., Zavala, M. A., Stoffel, M., Ballesteros‐Cánovas, J. A., Sancho-García, C., & Madrigal‐González, J. (2021) · Trees · doi:10.1007/s00468-021-02109-8 · Cited by 41
Carried away by a moonlight shadow: activity of wild boar in relation to nocturnal light intensity
Gordigiani, L., Viviano, A., Brivio, F., et al. (2021) · Mammal Research · doi:10.1007/s13364-021-00610-6 · Cited by 39
Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic
Roberts, S. M., Halpin, P. N., & Clark, J. S. (2022) · Scientific Reports · doi:10.1038/s41598-021-04110-0 · Cited by 40
Comparison of short term surgical outcomes of male and female gastrointestinal surgeons in Japan: retrospective cohort study
Okoshi, K., Endo, H., Nomura, S., Kono, E., Fujita, Y., Yasufuku, I., Hida, K., Yamamoto, H., Miyata, H., Yoshida, K., et al. (2022) · BMJ · doi:10.1136/bmj-2022-070568 · Cited by 41
Analysing spatio-temporal patterns of the global NO 2 -distribution retrieved from GOME satellite observations using a generalized additive model
Hayn, M., Beirle, S., Hamprecht, F. A., Platt, U., Menze, B. H., & Wagner, T. (2009) · Atmospheric chemistry and physics · doi:10.5194/acp-9-6459-2009 · Cited by 39
Environmental drivers of the anchovy/sardine complex in the Eastern Mediterranean
Katara, I., Pierce, G. J., Illian, J., & Scott, B. E. (2011) · Hydrobiologia · doi:10.1007/s10750-011-0693-5 · Cited by 37
Inter-breeding movements of little auks Alle alle reveal a key post-breeding staging area in the Greenland Sea
Mosbech, A., Johansen, K. L., Bech, N. I., et al. (2011) · Polar Biology · doi:10.1007/s00300-011-1064-4 · Cited by 39
Long-term population dynamics of Dactylorhiza incarnata (L.) Soó after abandonment and re-introduction of mowing
Schrautzer, J., Fichtner, A., Huckauf, A., et al. (2011) · Flora · doi:10.1016/j.flora.2010.11.008 · Cited by 39
Seasonal patterns of Pseudogymnoascus destructans germination indicate host–pathogen coevolution
Fischer, N. M., Dool, S. E., & Puechmaille, S. J. (2020) · Biology Letters · doi:10.1098/rsbl.2020.0177 · Cited by 38
Real-world effectiveness, its predictors and onset of action of cholinesterase inhibitors and memantine in dementia: retrospective health record study
Vaci, N., Koychev, I. G., Kim, C., Kormilitzin, A., Liu, Q., Lucas, C., Dehghan, A., Nenadić, G., & Nevado‐Holgado, A. J. (2020) · The British Journal of Psychiatry · doi:10.1192/bjp.2020.136 · Cited by 38
Landscape structure shapes activity levels and composition of aerial insectivorous bats at different spatial scales
Falcão, F. D. C., Dodonov, P., Caselli, C. B., dos Santos, J. S., & de Faria, D. M. (2021) · Biodiversity and Conservation · doi:10.1007/s10531-021-02210-x · Cited by 37
A Glyphosate-Based Herbicide Cross-Selects for Antibiotic Resistance Genes in Bacterioplankton Communities
da Costa, N. B., Hébert, M., Fugère, V., Terrat, Y., Fussmann, G. F., Gonzalez, A., & Shapiro, B. J. (2022) · mSystems · doi:10.1128/msystems.01482-21 · Cited by 39
Adaptive Probabilistic Forecasting of Electricity (Net-)Load
de Vilmarest, J., Browell, J., Fasiolo, M., et al. (2023) · IEEE Transactions on Power Systems · doi:10.1109/tpwrs.2023.3310280 · Cited by 38
Bees go up, flowers go down: Increased resource limitation from late spring to summer in agricultural landscapes
Bishop, G. A., Fijen, T. P. M., Raemakers, I., et al. (2024) · Journal of Applied Ecology · doi:10.1111/1365-2664.14576 · Cited by 38
Moving From CT to MRI Paradigm in Acute Ischemic Stroke: Feasibility, Effects on Stroke Diagnosis and Long-Term Outcomes
Rapillo, C. M., Dunet, V., Pistocchi, S., et al. (2024) · Stroke · doi:10.1161/strokeaha.123.045154 · Cited by 38
Bird Radar Validation in the Field by Time-Referencing Line-Transect Surveys
Dokter, A. M., Baptist, M. J., Ens, B. J., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0074129 · Cited by 38
Time use in travel surveys and time use surveys – Two sides of the same coin?
Gerike, R., Gehlert, T., & Leisch, F. (2015) · Transportation Research Part A Policy and Practice · doi:10.1016/j.tra.2015.03.030 · Cited by 40
The crs Package: Nonparametric Regression Splines for Continuous and Categorical Predictors
Nie, Z., & Jeffrey, S. R. (2012) · The R Journal · doi:10.32614/rj-2012-012 · Cited by 37
A comparative sensitivity analysis of human thermal comfort indices with generalized additive models
Charalampopoulos, I. (2019) · Theoretical and Applied Climatology · doi:10.1007/s00704-019-02900-1 · Cited by 38
Model Interpretation Through Lower-Dimensional Posterior Summarization
Woody, S., Carvalho, C. M., & Murray, J. S. (2020) · Journal of Computational and Graphical Statistics · doi:10.1080/10618600.2020.1796684 · Cited by 47
Changing expectations mediate adaptation in L2 production
Montero‐Melis, G., & Jaeger, T. F. (2019) · Bilingualism Language and Cognition · doi:10.1017/s1366728919000506 · Cited by 39
Development and Validation of a Model for Predicting the Risk of Acute Kidney Injury Associated With Contrast Volume Levels During Percutaneous Coronary Intervention
Huang, C., Li, S., Mahajan, S., et al. (2019) · JAMA Network Open · doi:10.1001/jamanetworkopen.2019.16021 · Cited by 38
Long‐term monitoring reveals decreasing water beetle diversity, loss of specialists and community shifts over the past 28 years
Roth, N., Zoder, S., Zaman, A. A., Thorn, S., & Schmidl, J. (2020) · Insect Conservation and Diversity · doi:10.1111/icad.12411 · Cited by 38
Extracurricular Activities and Chinese Children’s School Readiness: Who Benefits More?
Ren, L., Chen, J., Li, X., Wu, H., Fan, J., & Li, L. (2020) · Child Development · doi:10.1111/cdev.13456 · Cited by 39
Magnitude and time-course of excess mortality during COVID-19 outbreak: population-based empirical evidence from highly impacted provinces in northern Italy
Conti, S., Ferrara, P., Mazzaglia, G., D'Orso, M. I., Ciampichini, R., Fornari, C., Madotto, F., Magoni, M., Sampietro, G., Silenzi, A., et al. (2020) · ERJ Open Research · doi:10.1183/23120541.00458-2020 · Cited by 38
Evaluating structural and compositional canopy characteristics to predict the light‐demand signature of the forest understorey in mixed, semi‐natural temperate forests
Depauw, L., Perring, M. P., Landuyt, D., Maes, S. L., Blondeel, H., Lombaerde, E. D., Brūmelis, G., Brunet, J., Closset‐Kopp, D., Decocq, G., et al. (2020) · Applied Vegetation Science · doi:10.1111/avsc.12532 · Cited by 38
Warming winters threaten peripheral Arctic charr populations of Europe
Kelly, S., Moore, T. N., de Eyto, E., Dillane, M., Goulon, C., Guillard, J., Lasne, É., McGinnity, P., Poole, R., Winfield, I. J., et al. (2020) · Climatic Change · doi:10.1007/s10584-020-02887-z · Cited by 41
Reproductive senescence in a short‐lived fish
Žák, J., & Reichard, M. (2020) · Journal of Animal Ecology · doi:10.1111/1365-2656.13382 · Cited by 35
Estimating abundance and phenology from transect count data with GLMs
Edwards, C. B., & Crone, E. E. (2021) · Oikos · doi:10.1111/oik.08368 · Cited by 39
Photosynthetic plasticity of a tropical tree species, Tabebuia rosea , in response to elevated temperature and [ CO2 ]
Slot, M., Rifai, S. W., & Winter, K. (2021) · Plant Cell & Environment · doi:10.1111/pce.14049 · Cited by 38
Lifetime depression and age-related changes in body composition, cardiovascular function, grip strength and lung function: sex-specific analyses in the UK Biobank
Mutz, J., & Lewis, C. M. (2021) · Aging · doi:10.18632/aging.203275 · Cited by 36
A Scientific Basis for Regulating Deep-Sea Fishing by Depth
Clarke, J., Milligan, R. J., Bailey, D. M., et al. (2015) · Current Biology · doi:10.1016/j.cub.2015.07.070 · Cited by 38
Climatic conditions cause complex patterns of covariation between demographic traits in a long‐lived raptor
Herfindal, I., van de Pol, M., Nielsen, J. T., et al. (2014) · Journal of Animal Ecology · doi:10.1111/1365-2656.12318 · Cited by 38
Non-Life Insurance: Mathematics & StatisticsPreprint
Wüthrich, M. V. (2013) · SSRN Electronic Journal · doi:10.2139/ssrn.2319328 · Cited by 39
The importance of open science for biological assessment of aquatic environments
Beck, M. W., O’Hara, C. C., Lowndes, J. S., Mazor, R. D., Theroux, S. M., Gillett, D. J., Lane, B., & Gearheart, G. (2020) · PeerJ · doi:10.7717/peerj.9539 · Cited by 41
Operational Estimation of Landslide Runout: Comparison of Empirical and Numerical Methods
Peruzzetto, M., Mangeney, A., Grandjean, G., et al. (2020) · Geosciences · doi:10.3390/geosciences10110424 · Cited by 37
Re-examining the effects of drought on intimate-partner violence
Cooper, M., Sandler, A., Vitellozzi, S., Lee, Y., Seymour, G., Haile, B., & Azzarri, C. (2021) · PLoS ONE · doi:10.1371/journal.pone.0254346 · Cited by 38
Energy‐based step selection analysis: Modelling the energetic drivers of animal movement and habitat use
Klappstein, N. J., Potts, J. R., Michelot, T., Börger, L., Pilfold, N. W., Lewis, M. A., & Derocher, A. E. (2022) · Journal of Animal Ecology · doi:10.1111/1365-2656.13687 · Cited by 37
The effect of temperature on physical activity: an aggregated timeseries analysis of smartphone users in five major Chinese cities
Ho, J., Goggins, W. B., Mo, P. K. H., & Chan, E. Y. Y. (2022) · International Journal of Behavioral Nutrition and Physical Activity · doi:10.1186/s12966-022-01285-1 · Cited by 37
How regulatory focus–mode fit impacts variety‐seeking
Pham, T. N., Mathmann, F., Jin, H. S., & Higgins, E. T. (2022) · Journal of Consumer Psychology · doi:10.1002/jcpy.1317 · Cited by 43
Tree species growth response to climate in mixtures of Quercus robur/Quercus petraea and Pinus sylvestris across Europe - a dynamic, sensitive equilibrium
Vospernik, S., Heym, M., Pretzsch, H., Pach, M., Steckel, M., Aldea, J., Brazaitis, G., Bravo‐Oviedo, A., del Rı́o, M., Löf, M., et al. (2022) · Forest Ecology and Management · doi:10.1016/j.foreco.2022.120753 · Cited by 35
Direct and indirect effects of age on dengue severity: The mediating role of secondary infection
Annan, E., Treviño, J., Zhao, B., Rodriguez-Morales, A. J., & Haque, U. (2023) · PLoS neglected tropical diseases · doi:10.1371/journal.pntd.0011537 · Cited by 36
Dose-Dependent Association Between Body Mass Index and Mental Health and Changes Over Time
Chen, S., Zhang, H., Gao, M., Machado, D. B., Jin, H., Scherer, N., Sun, W., Sha, F., Smythe, T., Ford, T. J., et al. (2024) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2024.0921 · Cited by 44
Exploration of sample size and diatom-based indicator performance in three North American phosphorus training sets
Reavie, E. D., & Juggins, S. (2011) · Aquatic Ecology · doi:10.1007/s10452-011-9373-9 · Cited by 37
Juvenile Salmon Usage of the Skeena River Estuary
Carr‐Harris, C., Gottesfeld, A. S., & Moore, J. W. (2015) · PLoS ONE · doi:10.1371/journal.pone.0118988 · Cited by 37
Modeling Functional Data with Spatially Heterogeneous Shape Characteristics
Staicu, A., Crainiceanu, C. M., Reich, D. S., et al. (2011) · Biometrics · doi:10.1111/j.1541-0420.2011.01669.x · Cited by 37
Geodermatophilus poikilotrophisp. nov.: A Multitolerant Actinomycete Isolated from Dolomitic Marble
Montero‐Calasanz, M. D. C., Hofner, B., Göker, M., Rohde, M., Spröer, C., Hezbri, K., Gtari, M., Schümann, P., & Klenk, H. (2014) · BioMed Research International · doi:10.1155/2014/914767 · Cited by 37
Modelling trends in OH radical concentrations using generalized additive models
Jackson, L., Carslaw, N., Carslaw, D. C., et al. (2009) · Atmospheric chemistry and physics · doi:10.5194/acp-9-2021-2009 · Cited by 37
Mechanisms of Saccadic Suppression in Primate Cortical Area V4
Zanos, T. P., Mineault, P., Guitton, D., & Pack, C. C. (2016) · Journal of Neuroscience · doi:10.1523/jneurosci.1015-16.2016 · Cited by 37
Smokers’ strategies across social grades to minimise the cost of smoking in a period with annual tax increases: evidence from a national survey in England
Kuipers, M. A. G., Partos, T., McNeill, A. D., Beard, E., Gilmore, A., West, R., & Brown, J. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-026320 · Cited by 37
Spatiotemporal variation in thermal niches suggests lability rather than conservatism of thermal physiology along an environmental gradient
Gilbert, A. L., & Miles, D. B. (2019) · Biological Journal of the Linnean Society · doi:10.1093/biolinnean/blz093 · Cited by 36
Feeling the heat: Elevated temperature affects male display activity of a lekking grassland bird
Gudka, M., Santos, C. D., Dolman, P. M., Abad‐Gómez, J. M., & Silva, J. P. (2019) · PLoS ONE · doi:10.1371/journal.pone.0221999 · Cited by 37
Day Ahead Hourly Global Horizontal Irradiance Forecasting—Application to South African Data
Mpfumali, P., Sigauke, C., Bere, A., & Mulaudzi, S. T. (2019) · Energies · doi:10.3390/en12183569 · Cited by 37
Evidence for temperature-dependent shifts in spawning times of anadromous alewife ( Alosa pseudoharengus ) and blueback herring ( Alosa aestivalis )
Lombardo, S. M., Buckel, J. A., Hain, E. F., Griffith, E. H., & White, H. (2019) · Canadian Journal of Fisheries and Aquatic Sciences · doi:10.1139/cjfas-2019-0140 · Cited by 40
Deriving Stand Structural Complexity from Airborne Laser Scanning Data—What Does It Tell Us about a Forest?
Seidel, D., Annighöfer, P., Ehbrecht, M., Magdon, P., Wöllauer, S., & Ammer, C. (2020) · Remote Sensing · doi:10.3390/rs12111854 · Cited by 36
On the Interplay of Regional Mobility, Social Connectedness and The Spread of COVID-19 in Germany
Fritz, C., & Kauermann, G. (2021) · Journal of the Royal Statistical Society Series A (Statistics in Society) · doi:10.1111/rssa.12753 · Cited by 34
Poor Self-Reported Sleep is Related to Regional Cortical Thinning in Aging but not Memory Decline—Results From the Lifebrain Consortium
Fjell, A. M., Sørensen, Ø., Amlien, I. K., Bartrés‐Faz, D., Brandmaier, A. M., Buchmann, N., Demuth, I., Drevon, C. A., Düzel, S., Ebmeier, K. P., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa332 · Cited by 36
Google Trends Data and COVID‐19 in Europe: Correlations and model enhancement are European wide
Sulyok, M., Ferenci, T., & Walker, M. D. (2020) · Transboundary and Emerging Diseases · doi:10.1111/tbed.13887 · Cited by 34
Violent encounters between social units hinder the growth of a high-density mountain gorilla population
Caillaud, D., Eckardt, W., Vecellio, V., et al. (2020) · Science Advances · doi:10.1126/sciadv.aba0724 · Cited by 37
High Coral Bycatch in Bottom-Set Gillnet Coastal Fisheries Reveals Rich Coral Habitats in Southern Portugal
Dias, V., Oliveira, F., Boavida, J., et al. (2020) · Frontiers in Marine Science · doi:10.3389/fmars.2020.603438 · Cited by 37
Parametrisation of change-permitting extreme value models and its impact on the description of change
Prosdocimi, I., & Kjeldsen, T. (2020) · Stochastic Environmental Research and Risk Assessment · doi:10.1007/s00477-020-01940-8 · Cited by 37
Inferring UK COVID‐19 fatal infection trajectories from daily mortality data: Were infections already in decline before the UK lockdowns?
Wood, S. N. (2021) · Biometrics · doi:10.1111/biom.13462 · Cited by 37
Self-citation
Associations of Pre- and Postnatal Air Pollution Exposures with Child Blood Pressure and Modification by Maternal Nutrition: A Prospective Study in the CANDLE Cohort
Ni, Y., Szpiro, A. A., Young, M. T., Loftus, C. T., Bush, N. R., LeWinn, K. Z., Sathyanarayana, S., Enquobahrie, D. A., Davis, R. L., Kratz, M., et al. (2021) · Environmental Health Perspectives · doi:10.1289/ehp7486 · Cited by 36
Misidentifications in citizen science bias the phenological estimates of two hard‐to‐identify Elaenia flycatchers
Gorleri, F. C., & Areta, J. I. (2021) · Ibis · doi:10.1111/ibi.12985 · Cited by 38
Value of Information Analysis in Models to Inform Health Policy
Jackson, C. H., Baio, G., Heath, A., Strong, M., Welton, N. J., & Wilson, E. (2021) · Annual Review of Statistics and Its Application · doi:10.1146/annurev-statistics-040120-010730 · Cited by 36
Diverging incidence trends of oral tongue cancer compared to other head and neck cancers in young adults in France
Deneuve, S., Pérol, O., Dantony, E., et al. (2021) · International Journal of Cancer · doi:10.1002/ijc.33896 · Cited by 37
Language Models Explain Word Reading Times Better Than Empirical Predictability
Hofmann, M., Remus, S., Biemann, C., Radach, R. R., & Kuchinke, L. (2022) · Frontiers in Artificial Intelligence · doi:10.3389/frai.2021.730570 · Cited by 37
Optical coherence tomography reveals retinal thinning in schizophrenia spectrum disorders
Boudriot, E., Schworm, B., Slapakova, L., Hanken, K., Jäger, I. M., Stephan, M., Gabriel, V., Ioannou, G., Melcher, J., Hasanaj, G., et al. (2022) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-022-01455-z · Cited by 40
Comparison of PROSAIL Model Inversion Methods for Estimating Leaf Chlorophyll Content and LAI Using UAV Imagery for Hemp Phenotyping
Impollonia, G., Croci, M., Blandinières, H., Marcone, A., & Amaducci, S. (2022) · Remote Sensing · doi:10.3390/rs14225801 · Cited by 38
The effect of fire severity on first-year seedling establishment in a Pinus canariensis forest on Tenerife, Canary Islands
Otto, R., García‐del‐Rey, E., Muñoz, P. G., et al. (2009) · European Journal of Forest Research · doi:10.1007/s10342-009-0347-6 · Cited by 37
Characterization of winter foraging locations of Adélie penguins along the Western Antarctic Peninsula, 2001-2002
Erdmann, E. S., Ribic, C., Patterson-Fraser, D., & Fraser, W. (2011) · Deep Sea Research Part II Topical Studies in Oceanography · doi:10.1016/j.dsr2.2010.10.054 · Cited by 40
Meta-analytic structural equation modeling (MASEM): new tricks of the trade
Steinmetz, H., & Block, J. (2022) · Management Review Quarterly · doi:10.1007/s11301-022-00293-6 · Cited by 38
Open-ended cumulative cultural evolution of Hollywood film crews
Tinits, P., & Sobchuk, O. (2020) · Evolutionary Human Sciences · doi:10.1017/ehs.2020.21 · Cited by 36
Co-existence between humans and nature: Heritage trees in China’s yangtze River region
Jin, C., Zheng, M., Huang, L., Qian, S., Jim, C. Y., Lin, D., Zhao, L., Minor, J., Coggins, C., Chen, B., et al. (2020) · Urban forestry & urban greening · doi:10.1016/j.ufug.2020.126748 · Cited by 39
Predicting species abundance by implementing the ecological niche theory
de la Fuente, A., Hirsch, B. T., Cernusak, L. A., et al. (2021) · Ecography · doi:10.1111/ecog.05776 · Cited by 36
Predicting site-specific economic optimal nitrogen rate using machine learning methods and on-farm precision experimentation
de Lara, A., Mieno, T., Luck, J. D., & Puntel, L. A. (2023) · Precision Agriculture · doi:10.1007/s11119-023-10018-8 · Cited by 38
Pan‐European Landslide Risk Assessment: From Theory to Practice
Caleca, F., Lombardo, L., Steger, S., et al. (2025) · Reviews of Geophysics · doi:10.1029/2023rg000825 · Cited by 36
Human thalamocortical structural connectivity develops in line with a hierarchical axis of cortical plasticity
Sydnor, V. J., Bagautdinova, J., Larsen, B., Arcaro, M. J., Barch, D. M., Bassett, D. S., Alexander‐Bloch, A. F., Cook, P. A., Covitz, S. C., Franco, A. R., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01991-6 · Cited by 57

Authors: Wood, S. N.
Corresponding author: Wood, Simon N.
Venue: Chapman & Hall/CRC eBooks
Publisher: Chapman and Hall/CRC
Published: 2017-05-18
DOI: 10.1201/9781315370279
OpenAlex: W3112717819
Cited by: 13,852
References: 0
Citations by year: 2026: 1378 · 2025: 1355 · 2024: 1085 · 2023: 934 · 2022: 976 · 2021: 1373 · 2020: 1048 · 2019: 787 · 2018: 603 · 2017: 556
FWCI: 208.09
Type: book
Language: en
Open access: closed
Locations: Chapman & Hall/CRC eBooks (publishedVersion)
Topics: Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Inference
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords: generalized additive models, penalized spline regression, linear mixed models, generalized linear models, linear models, R software, nonparametric regression

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Generalized Additive Models: An Introduction with R

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cited by

Related

Metadata

Record

About these checks