试图使用金字塔的自动arima功能,却无处可寻。
导入整个类:
import pyramid
stepwise_fit = auto_arima(df.Weighted_Price, start_p=0, start_q=0, max_p=10, max_q=10, m=1,
start_P=0, seasonal=True, trace=True,
error_action='ignore', # don't want to know if an order does no
我试图导入这些库:
from math import sqrt
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
from statsmodels.tsa.arima_model import ARIMA
from sklearn.metrics import mean_absolute_error, mean_squared_error
from pyramid.arima import auto_arima
from statsmodels.tsa.stattools import adfuller
我使用远程访问的jupyter笔记本,并希望为auto_arima导入pmdarima以选择arima模型。如何通过远程访问安装pmdarima?
进口auto_arima包
from pmdarima import auto_arima
结果:
ModuleNotFoundError: No module named 'pmdarima'
对结构使用setter函数,但未按预期工作:
package main
import "fmt"
type T struct { Val string }
// this setter seems not to work
func (t T) SetVal( s string ) {
t.Val = s
}
// this setter, using ptr to T, seems to work ok
func (t *T) SetVal2( s string ) {
(*t).Val = s
}
func main() {
我有以下事实,它描述了世界杯的数据库
% host(X) <- X is the host country of World Cup
host('South Africa').
% federation (X,Y) <- X is the federation and Y is the numbers of countries in federation X
% qualified for World Cup.
federation('AFC',4).
federation('UEFA', 10).
federation('C
我正试图通过前一个月的学习来预测到月底的日收入。由于工作日和周末的收入行为不同,我决定在Python中使用时间序列模型(ARIMA)。
这是我正在使用的Python代码:
import itertools
import pandas as pd
import numpy as np
from datetime import datetime, date, timedelta
import statsmodels.api as sm
import matplotlib.pyplot as plt
plt.style.use('fivethirtyeight')
import ca
Windows 7 cmd shell中是否有方法在保持stderr流不变的同时将stderr重定向到stdout?
例如,我有一个程序输出到stderr和stdout以下消息
TO STDOUT
TO STDERR
我希望有两个包含以下内容的文件stderr.txt和stdout.txt
stderr.txt TO STDERR stdout.txt TO STDOUT TO STDERR
这个是可能的吗?
我对python还很陌生,并且一直致力于将ARIMA测试的结果输入到一个数据帧的过程中。因此,我通过编写以下代码获得了ARIMA结果:
for param in pdq:
for param_seasonal in seasonal_pdq:
try:
mod = sm.tsa.statespace.SARIMAX(df_month.Weighted_Price_box,
order=param,