Arma Models with Double-Exponentially Distributed Noise
推导了噪声为双指数（拉普拉斯）分布时标准自回归移动平均模型观测值的边际和双变量分布，并将其应用于硫酸盐浓度周度数据，发现比高斯模型拟合更好。
SUMMARY The marginal and bivariate distributions of the observations generated from a standard autoregressive moving average scheme are derived, assuming the noise to have a double-exponential (Laplace) distribution. The distributions may differ substantially from their Gaussian counterparts. The AR(1) model with double-exponential noise is applied to a series of weekly measurements of sulphate concentration and is shown to give a significantly better fit when compared with the Gaussian model.