Estimación del rendimiento de orellana mediante modelos Gamlss
Estimation of orellana yield through Gamlss models
DOI:
https://doi.org/10.15446/rev.fac.cienc.v6n1.61119Keywords:
GAMLSS, regresión, modelación, distribución gamma (es)GAMLSS, regression, modeling, gamma distribution (en)
Downloads
The influence of environmental variables on the production of edible mushrooms has been previously documented in the scientic literature. However, all these studies have in common the use of statistical models where the variable production is distributed in a normal way, although it is well known this is not always true. In this paper, we have used the GAMLSS (Generalized Additive Model for Location Scale and Shape) to study the in uence of variables such as humidity, temperature, aeration time, type of substrate and amount of substrate on the production of the Orellana mushroom. GAMLSS allows to assume statistical distributions for the response variable different from normal and enable modeling all parameters according to variables. When applying GAMLSS to the Orellana data, it was found that only the variables temperature, aeration time and type of substrate were influential on the Orellana production. In particular, the analysis revealed that at higher temperatures and aeration times the production of Orellana rises. Additionally, it was estimated that the production of Orellana would double if ground husk were used. The impact of results derived from this investigation can be utilized not just to quantify the effects of environmental variables on the industrial production of Orellana, but also to determine optimal factor combinations to maximize production.
References
Akaike, H. (1974). A new look at the statistical model identication. IEEE Transactions on Automatic Control, 19 (6), 716-723.
Akaike, H. (1983). Information measures and model selection. Bulletin of the International Statistical Institute, 50, 277-290.
Bonet, J., Pukkala, T., Fisher, C., Palahí, M., Martínez de Aragón, J. & Colinas, C. (2008). Empirical models for predicting the production of wild mushrooms in Scots pine (Pinus sylvestris L.) forests in the Central Pyrenees. Annals of Forest Science, Springer Verlag/EDP Sciences.
Buuren, S. (2001). An S Plus Program for drawing the Worm plot. [Consultada en noviembre de 2016]. Disponible en: http://www.stefvanbuuren.nl/wormplot/wp.SSC.txt.
Buuren, S. & Fredriks, M. (2001). Worm plot: a simple diagnostic device for modelling growth reference curves. Statistics in Medicine, 20, 1259-1277.
Cañedo, J. (2012). Cultivo de Pleurotus ostreatus en el valle de el Fuerte, Sinaloa: una alternativa de aprovechamiento de esquilmos agrícolas. (Tesis de doctorado). Universidad Autónoma Indígena de México, Sinaloa, México.
Cardona, A. (2011). Colección Buenas Prácticas, Hongos tipo ostra. FAO, Organización de las Naciones Unidas para la Alimentación y la Agricultura.
Cervantes, N. (2015). Cultivando setas de la especie pleurotus pulmonarius en el interior de las viviendas como un modelo empresarial que le permitirá a las victimas del desplazamiento forzado la superación de su vulnerabilidad y propiciar su reinclusión social. Revista de la Asociación Colombiana de Ciencias Biológicas, 27, 80-87.
de Castro, M.; Cancho, V. & Rodrigues, J. (2010). A hands-on approach for tting longterm survival models under the GAMLSS framework. Computer Methods and Programs in Biomedicine, 97 (2), 168-177.
Dunn, P. K. & Smyth, G. K. (1996). Randomized quantile residuals. Journal of Computational and Graphical Statistics, 5 (3), 236-244.
Gilchrist, R.; Stasinopoulos, D.; Rigby, R.; Sedgwick, J. & Voudouris, V. (2011). Forecasting Film Revenues Using GAMLSS. Proceedings of the 26th International Workshop on Statistical, Modelling. Disponible en: https://ssrn.com/abstract=1782783.
Hernández, R.; López, C. & Suárez, C. (2006). Evaluación de crecimiento y producción de pleurotus ostreatus sobre diferentes residuos agroindustriales del departamento de Cundinamarca (Tesis de pregrado). Ponticia Universidad Javeriana, Bogotá, Colombia.
Hernández, F.; Torres, M.; Arteaga, L. & Castro, C. (2015). GAMLSS models applied in the treatment of agro-industrial waste. Comunicaciones en Estadística, 8 (2), 245-254.
Martínez, F., de Miguel, S., Pukkala, T., Bonet, J., Ortega, P., Aldea, J. & Martínez, J. (2012). Yield models for ectomycorrhizal mushrooms in Pinus sylvestris forests with special focus on Boletus edulis and Lactarius group deliciosus. Forest Ecology and Management, 282, 63-69.
R Core Team (2017). R: A Language and Environmental for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org/.
Rigby, B. & Stasinopoulos, M. (2005). Generalized additive models for location scale and shape. Applied Statistics, 54 (3), 507-554.
Sandercock G., Voss C.; Cohen D., Taylor M. & Stasinopoulos D. M. (2012). Centile curves and normative values for the twenty metre shuttle-run test in English schoolchildren. Journal of Sports Sciences, 30 (7), 679-687.
Scandroglio, G., Gori, A., Vaccaro, E. & Voudouris, V. (2013). Estimating VaR and ES of the spot price of oil using futures-varying centiles. International Journal of Financial Engineering and Risk Management, 1 (1), 6-19.
Schwarz, G. (1978). Estimating the dimension of a model. Annals of Statistics, 6 (2), 461-464.
Sierra, F. & Orozo, J. (2014). Sistema de cultivo para la gestión de hongos comestibles como complemento alimenticio dirigido a los habitantes de la Comuna 18 de Cali para mejorar la seguridad alimentaria causada por la inaccesibilidad (Tesis de pregrado). Universidad Icesi, Santiago de Cali, Colombia.
Stasinopoulos, M., Rigby, B. & Akantziliotou, A. (2008). Instructions on how to use the gamlss package in R. [Consultado en noviembre de 2016].
Tahvanainen, V., Miina, J., Kurttila, M. & Salo, K. (2016). Modelling the yields of marketed mushrooms in Picea abies stands in eastern Finland. Forest Ecology and Management, 362, 79-88.
Tong, E. N., Mues, C. & Thomas, L. C. (2013). A zero-adjusted gamma model for mortgage loan loss given default. International Journal of Forecasting, 29, 548-562.
Velasco, E., Zamora, M., Nieto, C., Martnez, J. & Montoya, A. (2010). Modelos predictivos de la producción de hongos silvestres comestibles en bosques de coníferas, Tlaxcala, México. Revista Mexicana de Ciencias Forestales, 1 (1), 95-104.
How to Cite
APA
ACM
ACS
ABNT
Chicago
Harvard
IEEE
MLA
Turabian
Vancouver
Download Citation
License
Copyright (c) 2017 Revista de la Facultad de Ciencias
![Creative Commons License](http://i.creativecommons.org/l/by-nc-nd/4.0/88x31.png)
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
The authors or copyright holders of each paper confer to the Journal of the Faculty of Sciences of Universidad Nacional de Colombia a non-exclusive, limited and free authorization on the paper that, once evaluated and approved, is sent for its subsequent publication in accordance with the following characteristics:
- The corrected version is sent according to the suggestions of the evaluators and it is clarified that the paper mentioned is an unpublished document on which the rights are authorized and full responsibility is assumed for the content of the work before both the Journal of the Faculty of Sciences, Universidad Nacional de Colombia and third parties.
- The authorization granted to the Journal will be in force from the date it is included in the respective volume and number of the Journal of the Faculty of Sciences in the Open Journal Systems and on the Journal’s home page (https://revistas.unal.edu.co/index.php/rfc/index), as well as in the different databases and data indexes in which the publication is indexed.
- The authors authorize the Journal of the Faculty of Sciences of Universidad Nacional de Colombia to publish the document in the format in which it is required (printed, digital, electronic or any other known or to be known) and authorize the Journal of the Faculty of Sciences to include the work in the indexes and search engines deemed necessary to promote its diffusion.
- The authors accept that the authorization is given free of charge, and therefore they waive any right to receive any emolument for the publication, distribution, public communication, and any other use made under the terms of this authorization.
- All the contents of the Journal of the Faculty of Sciences are published under the Creative Commons Attribution – Non-commercial – Without Derivative 4.0.License
MODEL LETTER OF PRESENTATION and TRANSFER OF COPYRIGHTS
Personal data processing policy
The names and email addresses entered in this Journal will be used exclusively for the purposes set out in it and will not be provided to third parties or used for other purposes.