Estimating the water quality parameters of Davao river station 6 - A time series regression approach /
Jinayon, Daisy C.
Estimating the water quality parameters of Davao river station 6 - A time series regression approach / Daisy C. Jinayon - 2005 - 65 leaves
Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2005
Time series regression model was developed representing each of the water quality parameters of the Davao River Station 6 namely the temperature, pH, dissolved oxygen, biochemical oxygen demand and total dissolved solids using the quarterly data obtained from the Environment Management Bureau (EMB). Of Region XI. The model estimated the values of the water quality parameters of Davao River Station 7 as the independent variable. Each of the water quality parameters passed the stationarity test using the time series plot and the correlogram test (that is through computing the autocorrelation function (ACF) and the partial autocorrelation function (PACF). Using the model obtained, the one period ahead forecast was done in each of the water quality parameters of Station 6 except for the settleable matter, total solids, and total suspended solids. The models can serve as guide in making plans of action to protect the water quality of Station 6 from potential contamination, which I mainly caused by the parameter values of Station 7 and 8.
Undergraduate Thesis --AMAT200
Estimating the water quality parameters of Davao river station 6 - A time series regression approach / Daisy C. Jinayon - 2005 - 65 leaves
Thesis (BS Applied Mathematics) -- University of the Philippines Mindanao, 2005
Time series regression model was developed representing each of the water quality parameters of the Davao River Station 6 namely the temperature, pH, dissolved oxygen, biochemical oxygen demand and total dissolved solids using the quarterly data obtained from the Environment Management Bureau (EMB). Of Region XI. The model estimated the values of the water quality parameters of Davao River Station 7 as the independent variable. Each of the water quality parameters passed the stationarity test using the time series plot and the correlogram test (that is through computing the autocorrelation function (ACF) and the partial autocorrelation function (PACF). Using the model obtained, the one period ahead forecast was done in each of the water quality parameters of Station 6 except for the settleable matter, total solids, and total suspended solids. The models can serve as guide in making plans of action to protect the water quality of Station 6 from potential contamination, which I mainly caused by the parameter values of Station 7 and 8.
Undergraduate Thesis --AMAT200