suppose I have a dataset like this

suppose I have a dataset like this

Closed 3 days ago.

Suppose I have a standardized data frame and I performed clustering using the R package diceR. The input format of the data frame and the clustering code are as follows. After clustering, I selected k = 9 as the result based on the silhouette coefficient. I have seen literature that suggests using the clusterboot function from the fpc package for resampling and calculating Jaccard similarity to evaluate the stability of the clustering. How can this method be implemented in R? Are there any better methods?

Closed 2 days ago.

I observed slight differences in the parameter estimates when fitting a model with different specifications for the sample weights. One one hand I specified the weights in glm on the other I used survey package. While the point estimates were similar across both methods, the confidence intervals and p-values varied significantly. What could account for these discrepancies? Note: I used tbl_regression and tbl_merge from the gtsummary to present the estimate nicely.

Say we have a data.frame with different data types, not just numbers but perhaps text as well:

Say we have a data.frame with different data types, not just numbers but perhaps text as well:

I’m looking for help in disaggregating some spatial data into smaller grid cells.

I want to forecast my data by R and using varmax model multivariate time series , i have this code i want to chck is it true ?