[英]How to Interpret a Coefficient table for Multinom() Function in R
I have a dataset that has weather=0 if temp is <65 degrees Fahrenheit, weather = 1 if temp is =65 degrees Fahrenheit, and weather = 2 if temp is >68 degrees Fahrenheit.我有一个数据集,如果温度 <65 华氏度,天气 = 0,如果温度 = 65 华氏度,天气 = 1,如果温度 > 68 华氏度,天气 = 2。 I need to estimate a probability that the temp is between 65 <= weather < 68 degrees Fahrenheit, given the days = 20. Here is the formula and output我需要估计温度在 65 <= 天气 < 68 华氏度之间的概率,给定天数 = 20。这是公式和 output
multinom(formula = weather ~ days, data = USWeather13)
Which gives the coefficient table:其中给出了系数表:
Coefficients:
(Intercept) days
1 5.142 -.252
2 25.120 .343
Std. Errors:
(Intercept) days
1 1.742 .007
2 1.819 .004
Does anyone know how I can interpret this or figure out this problem?有谁知道我如何解释这个或找出这个问题?
In your example, weather=0
is the reference level, and you have the coefficients as the log odds ratio of weather=1
or weather=2
for every unit of your predictor Days
.在您的示例中, weather=0
是参考水平,并且您将系数作为预测变量Days
的每个单位的weather=1
或weather=2
的对数优势比。
It's an example without the complete information, but reading your coefficients, it means for every unit increase in days, you reduce the log-odd probability of 1 vs 0 by -.252 and log-odd probability of 2 vs 0 by.343.这是一个没有完整信息的示例,但是阅读您的系数,这意味着对于每增加一个单位的天数,您将 1 对 0 的对数奇数概率降低 -.252,将 2 对 0 的对数奇数概率降低.343。
If you need to figure the respective probabilities at days=20, you do:如果您需要计算 days=20 时的相应概率,您可以:
fit = multinom(formula = weather ~ days, data = USWeather13)
predict(fit,newdata=data.frame(days=20),type="prob")
Think this website might provide a good guide on how to interpret the coefficients.认为这个网站可能会为如何解释系数提供一个很好的指南。
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