This paper describes stochastic modeling of pencoordinate information in HMMs with structured character pattern representation (SCPR) for on-line recognition of handwritten Japanese characters. SCPR allows HMMs for Kanji character patterns to share common subpatterns. Although SCPR-based HMMs have been successfully applied to Kanji character recognition, the pen-coordinate feature has not been modeled since it is an unique feature for each character pattern. In this paper, we employ mapping from a common subpattern to each occurrence in Kanji patterns in the estimation step of SCPR-based HMMs. We also employ adaptation of state parameters to each character pattern in generating character HMMs by composing SCPR-based HMMs. Experimental results showed that the correct recognition rate improved from 83.6% to 92.3% for Japanese Kanji character patterns by modeling the pen-coordinate information in the SCPRbased HMMs.