Resultados de búsqueda - Random variables.

Estimating returns to soil conservation adoption in the northern Ethiopian highlands por Kassie, M., Pender, J.L., Yesuf, M., Kohlin, G., Bulffstone, R., Mulugeta, E.

“…We use matching methods, random effects, and Mundlak's approach to control selection and endogeneity bias that may arise due to correlation of unobserved heterogeneity and observed explanatory variables. …”
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Estimating seroprevalence and variation to four tick-borne infections and determination of associated risk factors in cattle under traditional mixed farming system in Mbeere Distri... por Gachohi, John M., Ngumi, P.N., Kitala, P.M., Skilton, Robert A.

“…A total of 440 cattle in 80 farms, selected by stratified random sampling from the four divisions in the district, were surveyed. …”
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Host tree-based scenario modelling for predicting a key edible insect, mopane worm Gonimbrasia belina (Westwood, 1894) distribution in Southern Africa por Meltus, Q., Mudereri, B.T., Mutamiswa, R., Abdel-Rahman, E.M., Matunhu, J., Musundire, R., Niassy, S., Tonnang, H.

“…To assess their relative importance, the study compared models incorporating various mopane worm host trees and predictor variables. Using the species distribution modelling (SDM) package in R, an ensemble of random forest (RF), support vector machine (SVM), and boosted regression tree (BRT) algorithms were used to assess the spatial extent of mopane worm distribution in Southern Africa. …”
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Impact of soil conservation on crop production in the Northern Ethiopian Highlands por Kassie, Menale, Pender, John L., Yesuf, Mahmud, Kohlin, Gunnar, Bluffstone, Randy, Mulugeta, Elias

“…Here, we use matching methods, random effects and Mundlak’s approach to control for selection and endogeneity biases that may arise due to correlation of unobserved heterogeneity and observed explanatory variables. …”
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Graphical approaches to support the analysis of linear-multilevel models of lamb pre-weaning growth in Kolda (Senegal) por Lancelot, R., Lesnoff, Matthieu, Tillard, E., McDermott, John J.

“…This study highlighted the usefulness of graphical methods in their analysis through: (1) the choice of the fixed and random effects and their structure, (2) the assessment of goodness-of-fit and (3) distributional assumptions for random effects and residuals. …”
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Determinants of land use change: evidence from a community study in Honduras por Bergeron, Gilles, Pender, John L.

“…A 20-year historical timeline (1975-1995) is constructed for the village of La Lima in central Honduras, based on a random sample of 97 plots. Changes in land use are examined using transition analysis and multinomial logit analysis. …”
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Determinants of credit repayment and fertilizer use by cooperative members in Ada District, East Shoa Zone, Oromia Region por Mijena, A.

“…Data for this study were collected both from primary and secondary sources during 2009. A two-stage random sampling procedure was adopted to select five agricultural cooperatives and a total of 130 sample respondents from the district. …”
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Searching for manatees in the dark waters of a transboundary river between Mexico and Belize: a predictive distribution model por Corona-Figueroa, M. Fabiola, Ríos, Ney, Castelblanco-Martínez, Delma N, Vilchez-Mendoza, Sergio J, Delgado-Rodríguez, Diego, Niño-Torres, Carlos A

“…We characterize and determine the ecohydrological variables influencing the presence and habitat use of manatees in the Hondo River. …”
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Replication Data for: The impact of climate change on cacao production in Central America and the Caribbean por Bunn, Christian, Lundy, Mark M., Castro-Llanos, Fabio Alexander

“…This analysis was done with a machine learning approach: Random Forest model, which took into account climatic variables, such as precipitation, temperature and evapotranspiration. …”
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Household Endowments and Poverty Reduction in Rural Nigeria: Evidence from Rice Farming Households por Awotide, B.A., Diagne, A., Awoyemi, T.T., Ojehomon, V.E.T.

“…A total of 600 rice farmers selected through multistage random sampling techniques were interviewed with the aid of well structured questionnaires. …”
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Rice phenotyping using unmanned aerial vehicles: Analyzing morphological characteristics and yield por Goigochea Pinchi, Diego, Vega Herrera, Sergio Sebastian, Torres Chavez, Edson Esmith, Archentti Reategui, Fernando, Barrera Torres, Ciceron, Dominguez Yap, Percy Luis, Ysuiza Perez, Alfredo, Perez Tello, Monica, Rios Rios, Raúl, Santillan Gonzáles, Manuel Dante, Ganoza Roncal, Jorge Juan, Ruiz Reyes, Jose Guillermo, Agurto Piñarreta, Alex Ivan

“…The variables studied were plant height, number of panicles, number of tillers, and yield. …”
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Efecto del clima sobre la respuesta térmica en vacas de diferentes grupos raciales en trópico bajo por Molina-Benavides, Raúl Andrés, Perilla-Duque, Sandra, Campos-Gaona, Rómulo, Sánchez-Guerrero, Hugo, Rivera-Palacio, Juan Camilo, Muñoz-Borja, Luis Armando, Jiménez-Rodas, Daniel

“…The information was analyzed using descriptive statistics, correlation matrices and Random Forest models, through the R software. Results. …”
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Adoption of improved sesame varieties in Meisso District, West Hararghe Zone, Ethiopia por Gedefa, B.

“…At the second stage, four PAs were randomly selected among sesame growers PAs using random sampling method. …”
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Climate-informed agronomic advisories for maize in Colombia: Progress report for the Excellence in Agronomy (EiA) initiative Latin America Use Case por Diaz, Maria Victoria, Estrada, Oscar, Llanos, Lizeth, Ramírez Villegas, Julián Armando

“…The dataset used included 748 observations, and 45 explanatory variables, with the only response variable being maize yield, and covered the period 2013–2019. …”
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Determinants of productivity of smallholder farmers supplying cassava to starch processors in Nigeria: a baseline evidence por Ojiako, I.A., Tarawali, G., Okechukwu, R.U., Chianu, Jonas N.

“…Together the included variables explained 72.1% of the variation in the productivity model. …”
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A study of factors associated with the prevalence of coccidia infection in cattle and its spatial epidemiology in Busia, Bungoma and Siaya counties, Kenya por Makau, D.N.

“…Households were then selected randomly using ArcMap 2.0 software to generate random points (and a back-up for each random point) within the study area. …”
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Are estimates of calorie-income elasticities too high? a recalibration of the plausible range por Bouis, Howarth E., Haddad, Lawrence James

“…The wide range of calorie-income elasticities in the literature results, in large part, from the particular calorie and income variables used for estimation. Elasticities across four estimation techniques and four calorie-income variable pairs for a sample of Philippine farm households, ranged from 0.03 to 0.59. …”
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Market chain analysis of teff and wheat production in Halaba Special Woreda, southern Ethiopia por Urgessa, M.

“…Primary data were collected from160 teff and wheat producers and 43 grain traders based on two stage random sampling method. Multiple linear regression model was employed to estimate the determinants of teff and wheat supply. …”
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Estimating the impact of agricultural support on farm price : an analysis of Swedish farm prices por Falkdalen, Maria

“…Factors like the quality of the land, agricultural structure, urbanisation, agricultural policies and residential characteristics were found to be important determinants of the price of agricultural land and farms and were therefore included as independent variables in the analysis. Data were analysed in STATA by multiple regression analysis where both pooled OLS, random effects and fixed effects regressions were used to determine the correlation between the independent variables and the dependent variable, the average farm price per municipality. …”

Global mapping of highly pathogenic avian influenza H5N1 and H5Nx clade 2.3.4.4 viruses with spatial cross-validation por Dhingra, Madhur S, Artois, Jean, Robinson, Timothy P., Linard, Catherine, Chaiban, Celia, Xenarios, Ioannis, Engler, Robin, Liechti, Robin, Kuznetsov, Dmitri, Xiao, Xiangming, Dobschuetz, Sophie Von, Claes, Filip, Newman, Scott H, Dauphin, Gwenaëlle, Gilbert, Marius

“…Best predictions are obtained using spatial predictor variables describing host distributions, rather than land use or eco-climatic spatial predictor variables, with a strong association with domestic duck and extensively raised chicken densities. …”
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