A linear predictive analysis method for obtaining a coefficient which can be converted into a linear predictive coefficient corresponding to an input time series signal for each frame which is a predetermined time interval, the input time series signal being a digital audio signal, a digital acoustic signal, an electrocardiogram, an electroencephalogram, a magnetic encephalography or a seismic wave, the linear predictive analysis method comprising: an autocorrelation calculating step of calculating autocorrelation R o (i) between the input time series signal X o (n) of a current frame and the input time series signal X o (n-i) i sample before the input time series signal X o (n) or the input time series signal X o (n+i) i sample after the input time series signal X o (n) for each of at least i = 0, 1,..., P max; and a predictive coefficient calculating step of obtaining a coefficient which can be converted into linear predictive coefficients from the first-order to the P max -order using modified autocorrelation R' o (i) obtained by multiplying the autocorrelation R o (i) by a coefficient w o (i) for each corresponding i, characterized in that the linear predictive analysis method further comprises a coefficient determining step of acquiring the coefficient w o (i) from one coefficient table among two or more coefficient tables using a value having positive correlation with a pitch gain based on the input time series signal of the current frame or a past frame assuming that a coefficient w o (i) is stored in each of the two or more coefficient tables, among the two or more coefficient tables, a coefficient table from which the coefficient w o (i) is acquired in the coefficient determining step when the value having positive correlation with the pitch gain is a first value is set as a first coefficient table, among the two or more coefficient tables, a coefficient table from which the coefficient w o (i) is acquired in the coefficient determining step when the value having positive correlation with the pitch gain is a second value which is smaller than the first value is set as a second coefficient table, for at least part of each order i, a coefficient corresponding to the each order i in the second coefficient table is greater than a coefficient corresponding to the each order i in the first coefficient table, and the pitch gain is a normalized correlation between signals with time difference by a pitch period for the input time series signal or a linear predictive residual signal of the input time series signal. an autocorrelation calculating step of calculating autocorrelation R o (i) between the input time series signal X o (n) of a current frame and the input time series signal X o (n-i) i sample before the input time series signal X o (n) or the input time series signal X o (n+i) i sample after the input time series signal X o (n) for each of at least i = 0, 1,..., P max; and a predictive coefficient calculating step of obtaining a coefficient which can be converted into linear predictive coefficients from the first-order to the P max -order using modified autocorrelation R' o (i) obtained by multiplying the autocorrelation R o (i) by a coefficient w o (i) for each corresponding i, characterized in that the linear predictive analysis method further comprises a coefficient determining step of acquiring the coefficient w o (i) from one coefficient table among two or more coefficient tables using a value having positive correlation with a pitch gain based on the input time series signal of the current frame or a past frame assuming that a coefficient w o (i) is stored in each of the two or more coefficient tables, among the two or more coefficient tables, a coefficient table from which the coefficient w o (i) is acquired in the coefficient determining step when the value having positive correlation with the pitch gain is a first value is set as a first coefficient table, among the two or more coefficient tables, a coefficient table from which the coefficient w o (i) is acquired in the coefficient determining step when the value having positive correlation with the pitch gain is a second value which is smaller than the first value is set as a second coefficient table, for at least part of each order i, a coefficient corresponding to the each order i in the second coefficient table is greater than a coefficient corresponding to the each order i in the first coefficient table, and the pitch gain is a normalized correlation between signals with time difference by a pitch period for the input time series signal or a linear predictive residual signal of the input time series signal.