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001			UPMIN-00000009285
003			UPMIN
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008			230213b |||||||| |||| 00| 0 eng d
040			_aDLC _cUPMin _dupmin
041			_aeng
090			_aLG993.5 2004 _bA64 Y34
100	1		_aYadao, Karla Jean D. _92449
245	0	0	_aPiecewise interpolation methods for equally spaced data points with observational errors / _cKarla Jean D. Yadao
260			_c2004
300			_a80 leaves
502			_aThesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2004
520	3		_aExperimental data came in discrete form in real world situations. These points may be interpolated to approximate the function. However, observational errors are always associated with experimental data. This study compared the performances of four piecewise interpolation methods, namely, piecewise linear, piecewise quadratic, a modified piecewise cubic polynomial and cubic spline in interpolating data points with random errors on four selected test functions. Random errors were generated based on two distribution functions (i.e. Gaussian distribution with parameters and and uniform distribution with range [a, b]). Piecewise linear performed best over the other hand, piecewise quadratic interpolation is better on small values of and smaller ranges. On oscillatory type of function, cubic spline performed best on small values of and smaller ranges. Moreover, the modified cubic polynomial performed best on very small values of and ranges used in generating random errors. As an illustration, the recommended method was applied to the data of monthly solid waste disposal of Davao City for CY 1996-2002 based solely on the collection of City Environment and Natural Resources Office (CENRO).
658			_aUndergraduate Thesis _cAMAT200, _2BSAM
905			_aFi
905			_aUP
942			_2lcc _cTHESIS
999			_c313 _d313