pyfan.gen.rand.randgrid.ar_draw_random_normal¶
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pyfan.gen.rand.randgrid.
ar_draw_random_normal
(fl_mu, fl_sd, it_draws, it_seed=None, it_draw_type=0, fl_lower_sd=- 3, fl_higher_sd=None)[source]¶ Draw a Vector of Possibly Sorted and Bounded Normal Shocks
- Parameters
- fl_mu, fl_sdfloat
The mean and standard deviation of the normal process
- it_draws: `int`
Number of Draws
- it_seed: `int`, optional
External random seed externally. Default is 123.
- it_draw_type: `int`, optional
Indicates which type of normal draws to make. 0 sorted normal draws cut off at bounds. 1 equi-quantile unequal distance points; 2 normal draws unsorted.
- fl_lower_sd, fl_higher_sdfloat
Impose lower and upper bounds (in sd units) on shock draws. The normal distribution does not have lower or upper bounds.
- Returns
- numpy.array of shape (1, it_draws)
A vector of sorted or unsorted random grid points, or equi-quantile points.
Notes
This method requires a dataset of equal-sized time series
Examples
>>> fl_mu = 0 >>> fl_sd = 1 >>> it_draws = 5 >>> it_seed = 123 >>> fl_lower_sd = -1 >>> fl_higher_sd = 0.8 >>> it_draw_type = 0 >>> ar_draw_random_normal(fl_mu, fl_sd, it_draws, ... it_seed, it_draw_type, ... fl_lower_sd, fl_higher_sd) [-1. 0.8 0.2829785 - 1. - 0.57860025]
>>> it_draw_type = 1 >>> ar_draw_random_normal(fl_mu, fl_sd, it_draws, ... it_seed, it_draw_type, ... fl_lower_sd, fl_higher_sd) [-1. - 0.47883617 - 0.06672597 0.3338994 0.8]
>>> it_draw_type = 2 >>> ar_draw_random_normal(fl_mu, fl_sd, it_draws, ... it_seed, it_draw_type, ... fl_lower_sd, fl_higher_sd) [-1. - 1. - 0.57860025 0.2829785 0.8]