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@@ -21,8 +21,8 @@ The implementation is based on the [Gaussian mixture models](https://scikit-lear
   - **use_amplitude** (default = True): If using amplitude information.
   - **vel** (default = {"p": 6.0, "s": 6.0 / 1.75}): velocity for P and S phases.
   - **use_dbscan**: If using dbscan to cut a long sequence of picks into segments. Using DBSCAN can significantly speed up associaiton using small windows. 
-  - **dbscan_eps** (default = 10.0s): The maximum time between two picks for one to be considered as a neighbor of the other. See details in [DBSCAN](https://https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)
-  - **dbscan_min_samples** (default = 3): The number of samples in a neighborhood for a point to be considered as a core point. See details in [DBSCAN](https://https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)
+  - **dbscan_eps** (default = 10.0s): The maximum time between two picks for one to be considered as a neighbor of the other. See details in [DBSCAN]([https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html])
+  - **dbscan_min_samples** (default = 3): The number of samples in a neighborhood for a point to be considered as a core point. See details in [DBSCAN](https://scikit-learn.org/stable/modules/generated/sklearn.cluster.DBSCAN.html)
   - **oversampling_factor** (default = 10): The initial number of clusters is determined by (Number of picks)/(Number of stations)/(Inital points) * (oversampling factor).
   - **initial_points** (default=[1,1,1] for (x, y, z) directions): Initial earthquake locations (cluster centers). For a large area over 10 degrees, more initial points are helpful, such as [2,2,1].
   - **covariance_prior** (default = (5, 5)): covariance prior of time and amplitude residuals. Because current code only uses an uniform velocity model, a large covariance prior can be used to avoid splitting one event into multiple events.