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kdensity command  (STATA Corporation)


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    STATA Corporation kdensity command
    Distribution of willingness to pay for in-situ soil nutrition surveillance technology. The nonparametric kernel density estimation was performed using the <t>kdensity</t> command in Stata. The distribution is highly skewed to the right indicating a great need for an alternative soil testing method. yy = 1 means that the first and second responses to the first and the second bids were both “yes”; yn = 2 means that the first and second responses to the first and the second bids were “yes” and “no” respectively; and ny = 3 means that the first and second responses to the first and the second bids were “no” and “yes” respectively; and nn = 4 means that the first and second responses to the first and the second bids were both “no” (see ESI 2 ).
    Kdensity Command, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/kdensity+command/kdensity+command/pmc11422606-291-9-12
    Average 90 stars, based on 1 article reviews
    kdensity command - by Bioz Stars, 2026-09
    90/100 stars

    Images

    1) Product Images from "Gendered farmer perceptions towards soil nutrition and willingness to pay for a cafetière-style filter system for in-situ soil testing: Evidence from Central Kenya"

    Article Title: Gendered farmer perceptions towards soil nutrition and willingness to pay for a cafetière-style filter system for in-situ soil testing: Evidence from Central Kenya

    Journal: Heliyon

    doi: 10.1016/j.heliyon.2024.e37568

    Distribution of willingness to pay for in-situ soil nutrition surveillance technology. The nonparametric kernel density estimation was performed using the kdensity command in Stata. The distribution is highly skewed to the right indicating a great need for an alternative soil testing method. yy = 1 means that the first and second responses to the first and the second bids were both “yes”; yn = 2 means that the first and second responses to the first and the second bids were “yes” and “no” respectively; and ny = 3 means that the first and second responses to the first and the second bids were “no” and “yes” respectively; and nn = 4 means that the first and second responses to the first and the second bids were both “no” (see ESI 2 ).
    Figure Legend Snippet: Distribution of willingness to pay for in-situ soil nutrition surveillance technology. The nonparametric kernel density estimation was performed using the kdensity command in Stata. The distribution is highly skewed to the right indicating a great need for an alternative soil testing method. yy = 1 means that the first and second responses to the first and the second bids were both “yes”; yn = 2 means that the first and second responses to the first and the second bids were “yes” and “no” respectively; and ny = 3 means that the first and second responses to the first and the second bids were “no” and “yes” respectively; and nn = 4 means that the first and second responses to the first and the second bids were both “no” (see ESI 2 ).

    Techniques Used: In Situ

    Related Articles

    In Situ:

    Article Title: Self-Consistent Density Estimation
    Article Snippet: We used an Epanechnikov kernel with Silverman’s optimal bandwidth rule (Silverman 1998), ho = 0.9min(σ, IQ/1.349)N − 15 (11) which is the default for both the kernel function and the bandwidth choice in Stata’s official kdensity command as well as the user-written kdens package (Jann 2005a).

    Article Title: Small area estimation of obesity prevalence and dietary patterns: a model applied to Rio de Janeiro city, Brazil.
    Article Snippet: We propose the use of previously developed small area estimation techniques to monitor obesity and dietary habits in developing countries and apply the model to Rio de Janeiro city.. We estimate obesity prevalence rates at the Census Tract through a combinatorial optimization spatial microsimulation model that matches body mass index and socio-demographic data in Brazil's 2008–9 family expenditure survey with Census 2010 socio-demographic data.. Obesity ranges from 8% to 25% in most areas and affects the poor almost as much as the rich.

    Article Title: Indexing Estimates of GFR to Body Surface Area in Low-Resource Settings With a High Burden of Malnutrition: Evidence From Guatemala
    Article Snippet: We calculated eGFR using the original and revised 2021 Chronic Kidney Disease–Epidemiology Collaboration (CKD-EPI) equations.2, 3 We calculated body surface area using the Dubois and Dubois formula.4 All analyses in this report were conducted at the individual-level without accounting for the survey weights used in the original report.1 We visualized differences between measured and calculated anthropometric indicators (height, weight, body mass index, body surface area) using the real distribution of data from the Guatemala survey to a same-sized simulated normal distribution derived from the means and standard deviations reported for the original CKD-EPI development cohort (kdensity and rnormal commands in Stata).

    Article Title: Gendered farmer perceptions towards soil nutrition and willingness to pay for a cafetière-style filter system for in-situ soil testing: Evidence from Central Kenya
    Article Snippet: The nonparametric kernel density estimation was performed using the kdensity command in Stata.

    Article Title: The labor market impact of relative body weight in Taiwan–a semiparametric analysis
    Article Snippet: This study investigates the impact of relative body weight on the wage of full-time workers using a semiparametric partially linear model, by age cohort and gender.. It defines relative body weight as relative BMI.. The data mainly come from the 2004, 2006 and 2008 Panel Study of Family Dynamics of Taiwan.



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    Image Search Results


    Distribution of willingness to pay for in-situ soil nutrition surveillance technology. The nonparametric kernel density estimation was performed using the kdensity command in Stata. The distribution is highly skewed to the right indicating a great need for an alternative soil testing method. yy = 1 means that the first and second responses to the first and the second bids were both “yes”; yn = 2 means that the first and second responses to the first and the second bids were “yes” and “no” respectively; and ny = 3 means that the first and second responses to the first and the second bids were “no” and “yes” respectively; and nn = 4 means that the first and second responses to the first and the second bids were both “no” (see ESI 2 ).

    Journal: Heliyon

    Article Title: Gendered farmer perceptions towards soil nutrition and willingness to pay for a cafetière-style filter system for in-situ soil testing: Evidence from Central Kenya

    doi: 10.1016/j.heliyon.2024.e37568

    Figure Lengend Snippet: Distribution of willingness to pay for in-situ soil nutrition surveillance technology. The nonparametric kernel density estimation was performed using the kdensity command in Stata. The distribution is highly skewed to the right indicating a great need for an alternative soil testing method. yy = 1 means that the first and second responses to the first and the second bids were both “yes”; yn = 2 means that the first and second responses to the first and the second bids were “yes” and “no” respectively; and ny = 3 means that the first and second responses to the first and the second bids were “no” and “yes” respectively; and nn = 4 means that the first and second responses to the first and the second bids were both “no” (see ESI 2 ).

    Article Snippet: The nonparametric kernel density estimation was performed using the kdensity command in Stata.

    Techniques: In Situ