The　inference　for　the　parameters　in　a　semiparametric　regression　model　is　studied　by　using　the　wavelet　and　the　bootstrap　methods.　The　bootstrap　statistics　are　constructed　by　using　Efron＇s　resampling　technique,　and　the　strong　uniform　convergence　of　the　bootstrap　approximation　is　proved.　Our　results　can　be　used　to　construct　the　large　sample　confidence　intervals　for　the　parameters　of　interest.　A　simulation　study　is　conducted　to　evaluate　the　finite-sample　performance　of　the　bootstrap　method　and　to　compare　it　with　the　normal　approximation-based　method.