英文:
Is there a way to calculate probability of detection for two separate datasets that have different ranges?
问题
我有两个不同的数据集，一个数据集的值范围从0到1（估计值），另一个数据集的值范围从-2到2（观测值）。我想知道估计数据集中的值是否等于或小于0.4，以及观测数据集中的值是否大于1。这两个数据集的长度也不同。对于这种情况，检测概率可能不是最好的选择...如果不是的话，什么是最好的选择？
我的数据如下：
估计数据（df1）df1<-data.frame(est=c(0.2327,0.2443,0.4988, 0.5823))
观测数据（df2）df2<-data.frame(obs=c(0.57,0.24,1.62))
我已经尝试了一些类似问题中找到的不同函数，但没有成功。
感谢您提供的任何帮助！
英文:
I have two different datasets, one with values ranging from 0 to 1(estimated) and the other from -2 to 2(observed). I want to know when values are equal to or less than 0.4 in the estimated dataset and when values are greater than 1 in the observed dataset. The datasets are also of differing lengths. Probability of detection may not be the best choice for this...if not what would be?
My data looks like this:
Estimated data (df1) df1<-data.frame(est=c(0.2327,0.2443,0.4988, 0.5823))
Observed Data (df2) df2<-data.frame(obs=c(0.57,0.24,1.62))
I have tried a few different functions I found on similar questions but without luck.
Thank you for any help you can provide!!
答案1
得分: 1
尝试这个：
library(dplyr)
filtered_df1 <- df1 %>% filter(est <= 0.4)
filtered_df2 <- df2 %>% filter(obs > 1)
英文:
Try this:
library(dplyr)
filtered_df1 <- df1 %>% filter(est <= 0.4)
filtered_df2 <- df2 %>% filter(obs > 1)
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