In the previous paper, we raised the inverse problem to estimate entry frequency from both of data on the number of visitors observed at every shopping site and data obtained by on-site trip chain survey. To solve this, we developed simultaneous estimation method of consumer's entry frequency and shop-around pattern. While large retailers usually count the number of visitors at their shops, small retailers are not likely to count total visit frequency at their sites. Thus it is almost impossible to collect total visit frequency data at every size of shopping site. We necessarily face with the incomplete data problem where total visit frequencies at some shopping sites are missing. Hence some extension of our previous method is needed to enable one to do simultaneous estimation of entry frequency and shop-around pattern under the condition of missing data. The purpose of this paper is to make an extension of our previous method to tackle this problem. We apply the extended method to actual case of Fukuoka City and shows that our extended inverse estimation method is effective and accurate enough to estimate the entry frequency and shop-around pattern under missing data.