Provided are a prediction device, a prediction method, and a computer program, which related to prediction method using Taguchi-method, and which reflect, in addition to a time difference model, trends in changes over time, thus further improving prediction accuracy. For example, the prediction device determines, from signal values stored in a time series and data for each item, whether or not the signal trend of the signal values has periodicity, and if the signal trend has not periodicity, then a signal period is selected on the basis of the most recent signal trend and the MD trend for each item, and Taguchi-method is used on the data for each item and the signal values in the selected signal period, and prediction is carried out.
Please help me write a proper abstract based on the patent claims. CLAIM: 1-5. (canceled) 6. A prediction device comprising: a recording section recording values relating to an event with which a plurality of factors are associated and the plurality of factors associated with the values as data for each of a plurality of items chronologically corresponding to the values; an operation section performing operation based on a value and a piece of data for an item read out from values and data recorded in the recording section, the piece of data being corresponding to the value; a determination section determining a presence or an absence of a periodicity in the trend of chronological change of the value during a recording period for the value recorded in the recording section; a period selection section selecting a period, within the recording period, having a same trend as the trend of chronological change of the value during a corresponding period earlier than the object period to be predicted by a predetermined period if the determination section determines that a periodicity is absent; a period discrimination section discriminating a period, within the period selected by the selection section, the period to which the data for the plurality of items during the corresponding period belongs; an item selection section for selecting a portion of items from the plurality of items on the basis of a factorial effect value, indicating the strength of a correlation between the data for items and changes of the value, derived from data for the plurality of items during the discriminated period and the value corresponding to a period later than the discriminated period by a predetermined period; and a prediction section predicting a prediction value relating to the event during an object period to be predicted by calculating the prediction value during the object period to be predicted on the basis of data for the items selected by the item selecting section during the corresponding period. 7. The prediction device according to claim 6, wherein the determination section comprises: a calculation section calculating an autocorrelation coefficient for each period by changing the period for the values recorded chronologically; and a peak determination section determining a presence or an absence of a peak in a distribution of the autocorrelation coefficient calculated for each period, and wherein the determination section is configured to determine a periodicity is present if it is determined that a peak is present. 8. The prediction device according to claim 6, wherein the period discrimination section comprises: a first calculation section calculating Mahalanobis's generalized distance of data for the plurality of items during the period selected by the selection section; and a second calculation section calculating a trend of the calculated Mahalanobis's generalized distance on the basis of a trend model, and wherein the period discrimination section is configured to discriminate a trend having a same trend as a trend of data for the plurality of items during the corresponding period, within the selected period by the selection section, as the period to which the data for the plurality of items during the corresponding period belongs. 9. A prediction method on a computer having a processor and a recording section for recording values relating to an event with a plurality of factors are associated and the plurality of factors associated with the values as data for each of a plurality of items chronologically corresponding to the values, the method comprising: determining a presence or an absence of a periodicity in a trend of chronological change of the value during a recording period for the value recorded in the recording section; selecting a period, within the recording period, the period having a same trend as the trend of chronological change of the value during a corresponding period earlier than the object period to be predicted by a predetermined period if it is determined that a periodicity is absent; discriminating a period, within the selected period, the period to which the data for the plurality of items during the corresponding period belongs; selecting a portion of the plurality of items on the basis of a factorial effect value derived from data for the plurality of items during the discriminated period and the value corresponding to a period later than from the discriminated period by a predetermined period; and calculating a prediction value during the object period to be predicted on the basis of data for the selected items during the corresponding period. 10. A non-transitory computer readable medium storing a computer program causing a computer having a recording section for recording values relating to an event with which a plurality of factors are associated and the plurality of factors associated with the values as data for each of a plurality of items chronologically corresponding to the values, the computer program comprising: determining a presence or an absence of a periodicity in the trend of chronological change of the value during a recording period for the value recorded in the recording section; selecting a period within the recording period, the period having a same trend as the trend of chronological change of the value during a corresponding period earlier than the object period to be predicted by a predetermined period when it is determined that a periodicity is absent; discriminating a period, within the selected period, the period to which the data for the plurality of items during the corresponding period belongs; selecting a portion of the plurality of items on the basis of a factorial effect value derived from data for the plurality of items during the discriminated period and the value corresponding to a period later than the discriminated period by a predetermined period; and calculating the prediction value during the object period to be predicted on the basis of data for the selected items during the corresponding period.