Dear R expert I am a student and I am currently conducting a research project on the Modeling Loss Index Triggers to price Cat Bonds: Application of the risk of hurricanes in USA. I need to solve with R (especially with EM algorithm) this specific problem below. CRAN Package archive doesn't seem to have it also the statistical modeling journal didn't contain a paper that implements this: I have two data samples. The first sample contains 64 depths for historical hurricanes happened in Florida between 1950 - 2008. The second sample contains only 48 losses associated to these hurricanes. This second data is missing 16 values of losses. Since 48 out 64 observations have information about hurricanes losses, it is necessary to treat the missing data of losses for a further analysis. So, I chose to make an EM-algorithm: 1- Experts in climatology describe that hurricanes losses are directly proportional to the depths of the hurricanes. Besides, statistically we observe a relationship between the two vectors (depths of hurricanes and losses). So the approach is to estimate the missing losses by means of the linear regression model x= á+ â yi + åi, where x (n x 1) is a vector of observations on the response variable and y (n x p) is the p explanatory variables. 2- An approach to deal with the missing data is the expectation -Maximum algorithm (EM) The expectation step: This algorithm consists of omitting the cases with missing data and running a regression on what remains. The regression coefficient will be used to estimate the missing data. The maximization step: After this estimation step, a new regression will be done over the complete data (including estimated values). With the new regression coefficients, the missing data is re-estimated. This process will continue until the estimates are adjusted to give model sampling error, ie it will not be a longer noticeable change. Does anyone have any ideas how to make this in R algorithm? Can you guide me to something already done? Or please help me to find the true code. Thank you in advance to consider my request Best regards Souad _________________________________________________________________ [[elided Hotmail spam]] [[alternative HTML version deleted]]