Preliminary Analysis of the Effect of Item Health on Price
By Andrew Whitaker
Abstract: In Rimworld, the effect of item health on the price when buying from or selling to traders has remained unclear. Analysis of the code has revealed an intended behavior, but confirmation of this behavior was not found. As such, using data collected from the community, an analysis was performed to determine the effect of item health on its market price.
Methodology: Data was gathered from the community and generated by normal play. All data was collected in the sheet here and was compiled into a pivot table. Each category was then divided by the price of an equivalent full-health good to obtain a percent. All percents were averaged and arranged in a table for analysis.
Data: As above, found here.
Results: As expected, there is a significant correlation between item health and price. However, the expected result of two distinct linear relationships (one for 0-30%, and one from 31-99%) was not found. When the data was broken into two sets (0-30% and 31-100%) both a linear and exponential trend line were attempted. In addition, the same two were performed for the entire data set. r^2 values are as follows:
This shows the surprising results that the best fit model for the current data is an exponential model, of the form PA= PB 0.0044 e6.285 H, where PA is the new, adjusted price, PB is the item's base (full-health) price, and H is the health in decimal form.
Conclusions:
The data appears to suggest that the above model is the best fit for the current data. However, it is worth noting that this model loses usefulness between 80% and 100%, as the model suggests higher than base price in that range. Furthermore, there is still a high degree of data spread; the addition of more data is likely to result in more accurate, better models. Further research is advised, though the current model may suffice for a temporary, working equation.
Notes:
Note that the data are dynamic; the adding of further data points will change the analysis on the spreadsheet. This is intended, as the project is still ongoing.
Also note that, for those wishing to review the data themselves, it is located at the above link, in the "Item Health Analysis" spreadsheet. The graphs are located in rows 200 through 260, Columns A-N.
Peer review is welcome, as are alternate models which may fit the data better; the community has helped me get this far, so anyone who sees an error or a place for improvement is welcome.
Finally, a huge thank you to all who have contributed data; right now we have about 1 400 data points, which is remarkable for people helping out in their free time. This couldn't have happened without you.
Further refinements are forthcoming; as more data is acquired, current analyses will be refined, and new ones performed.
By Andrew Whitaker
Abstract: In Rimworld, the effect of item health on the price when buying from or selling to traders has remained unclear. Analysis of the code has revealed an intended behavior, but confirmation of this behavior was not found. As such, using data collected from the community, an analysis was performed to determine the effect of item health on its market price.
Methodology: Data was gathered from the community and generated by normal play. All data was collected in the sheet here and was compiled into a pivot table. Each category was then divided by the price of an equivalent full-health good to obtain a percent. All percents were averaged and arranged in a table for analysis.
Data: As above, found here.
Results: As expected, there is a significant correlation between item health and price. However, the expected result of two distinct linear relationships (one for 0-30%, and one from 31-99%) was not found. When the data was broken into two sets (0-30% and 31-100%) both a linear and exponential trend line were attempted. In addition, the same two were performed for the entire data set. r^2 values are as follows:
Data Range | Linear r^2 | Exponential r^2 |
0-30% | 0.525 | 0.488 |
31-100% | 0.156 | 0.53 |
0-100% | 0.199 | 0.792 |
This shows the surprising results that the best fit model for the current data is an exponential model, of the form PA= PB 0.0044 e6.285 H, where PA is the new, adjusted price, PB is the item's base (full-health) price, and H is the health in decimal form.
Conclusions:
The data appears to suggest that the above model is the best fit for the current data. However, it is worth noting that this model loses usefulness between 80% and 100%, as the model suggests higher than base price in that range. Furthermore, there is still a high degree of data spread; the addition of more data is likely to result in more accurate, better models. Further research is advised, though the current model may suffice for a temporary, working equation.
Notes:
Note that the data are dynamic; the adding of further data points will change the analysis on the spreadsheet. This is intended, as the project is still ongoing.
Also note that, for those wishing to review the data themselves, it is located at the above link, in the "Item Health Analysis" spreadsheet. The graphs are located in rows 200 through 260, Columns A-N.
Peer review is welcome, as are alternate models which may fit the data better; the community has helped me get this far, so anyone who sees an error or a place for improvement is welcome.
Finally, a huge thank you to all who have contributed data; right now we have about 1 400 data points, which is remarkable for people helping out in their free time. This couldn't have happened without you.
Further refinements are forthcoming; as more data is acquired, current analyses will be refined, and new ones performed.