Predict method for the conjoint function
# S3 method for conjoint predict(object, pred_data = NULL, pred_cmd = "", conf_lev = 0.95, se = FALSE, interval = "confidence", dec = 3, envir = parent.frame(), ...)
| object | Return value from |
|---|---|
| pred_data | Provide the dataframe to generate predictions. The dataset must contain all columns used in the estimation |
| pred_cmd | Command used to generate data for prediction |
| conf_lev | Confidence level used to estimate confidence intervals (.95 is the default) |
| se | Logical that indicates if prediction standard errors should be calculated (default = FALSE) |
| interval | Type of interval calculation ("confidence" or "prediction"). Set to "none" if se is FALSE |
| dec | Number of decimals to show |
| envir | Environment to extract data from |
| ... | further arguments passed to or from other methods |
See https://radiant-rstats.github.io/docs/multivariate/conjoint.html for an example in Radiant
conjoint to generate the result
summary.conjoint to summarize results
plot.conjoint to plot results
#> Conjoint Analysis #> Data : mp3 #> Response variable : Rating #> Explanatory variables: Memory, Radio, Size, Price, Shape #> Prediction dataset : mp3 #> #> Memory Radio Size Price Shape Prediction #> 4GB No Small $50 Square 53.278 #> 6GB Yes Medium $50 Square 64.889 #> 4GB Yes Medium $100 Square 50.389 #> 8GB No Large $100 Square 67.611 #> 8GB No Small $150 Square 49.111 #> 6GB Yes Large $150 Square 24.722 #> 6GB No Small $50 Circular 74.278 #> 8GB Yes Large $50 Circular 93.889 #> 4GB Yes Small $100 Circular 65.889 #> 6GB No Medium $100 Circular 65.278 #> 8GB No Medium $150 Circular 60.278 #> 4GB Yes Large $150 Circular 30.389 #> 8GB Yes Medium $50 Rectangular 72.389 #> 4GB No Large $50 Rectangular 30.278 #> 8GB Yes Small $100 Rectangular 67.722 #> 6GB No Large $100 Rectangular 31.111 #> 6GB Yes Small $150 Rectangular 18.722 #> 4GB No Medium $150 Rectangular 2.778