def deploySQL(self):
    '\n    ---------------------------------------------------------------------------\n    Returns the SQL code needed to deploy the model.\n\n    Returns\n    -------\n    str\n        the SQL code needed to deploy the model.\n        '
    sql = self.deploy_predict_
    if ((self.parameters['d'] > 0) or ((self.parameters['D'] > 0) and (self.parameters['s'] > 0))):
        for i in range(0, (self.parameters['d'] + 1)):
            for k in range(0, max(((self.parameters['D'] + 1) * min(1, self.parameters['s'])), 1)):
                if ((k, i) != (0, 0)):
                    comb_i_d = ((math.factorial(self.parameters['d']) / math.factorial((self.parameters['d'] - i))) / math.factorial(i))
                    comb_k_D = ((math.factorial(self.parameters['D']) / math.factorial((self.parameters['D'] - k))) / math.factorial(k))
                    sql += ' + {} * LAG(VerticaPy_y_copy, {}) OVER (ORDER BY [VerticaPy_ts])'.format(((((- 1) ** ((i + k) + 1)) * comb_i_d) * comb_k_D), (i + (self.parameters['s'] * k)))
    return sql
---------------------------------------------------------------------------
Returns the SQL code needed to deploy the model.

Returns
-------
str
    the SQL code needed to deploy the model.
def deploySQL(self):
    '\n    ---------------------------------------------------------------------------\n    Returns the SQL code needed to deploy the model.\n\n    Returns\n    -------\n    str\n        the SQL code needed to deploy the model.\n        '
    sql = self.deploy_predict_
    if ((self.parameters['d'] > 0) or ((self.parameters['D'] > 0) and (self.parameters['s'] > 0))):
        for i in range(0, (self.parameters['d'] + 1)):
            for k in range(0, max(((self.parameters['D'] + 1) * min(1, self.parameters['s'])), 1)):
                if ((k, i) != (0, 0)):
                    comb_i_d = ((math.factorial(self.parameters['d']) / math.factorial((self.parameters['d'] - i))) / math.factorial(i))
                    comb_k_D = ((math.factorial(self.parameters['D']) / math.factorial((self.parameters['D'] - k))) / math.factorial(k))
                    sql += ' + {} * LAG(VerticaPy_y_copy, {}) OVER (ORDER BY [VerticaPy_ts])'.format(((((- 1) ** ((i + k) + 1)) * comb_i_d) * comb_k_D), (i + (self.parameters['s'] * k)))
    return sql