Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significant factor » significant factors (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
significant factor » significant factors (Expand Search)
-
1321
-
1322
-
1323
-
1324
-
1325
-
1326
-
1327
-
1328
-
1329
-
1330
Trends of incident opioid users, L-TOT users, and L-TOT discontinuers between 2009 and 2013.
Published 2025Subjects: -
1331
-
1332
-
1333
-
1334
-
1335
Absolute β convergence results.
Published 2025“…Instead, there was a significant β divergence, indicating that the gap between the Xi’an metropolitan agglomeration’s population agglomeration level and that of other metropolitan agglomerations is gradually widening. …”
-
1336
Conditional β convergence results.
Published 2025“…Instead, there was a significant β divergence, indicating that the gap between the Xi’an metropolitan agglomeration’s population agglomeration level and that of other metropolitan agglomerations is gradually widening. …”
-
1337
Markov transition probability matrix (k = 4).
Published 2025“…Instead, there was a significant β divergence, indicating that the gap between the Xi’an metropolitan agglomeration’s population agglomeration level and that of other metropolitan agglomerations is gradually widening. …”
-
1338
Markov transition probability matrix (k = 4).
Published 2025“…Instead, there was a significant β divergence, indicating that the gap between the Xi’an metropolitan agglomeration’s population agglomeration level and that of other metropolitan agglomerations is gradually widening. …”
-
1339
Regression results.
Published 2025“…Instead, there was a significant β divergence, indicating that the gap between the Xi’an metropolitan agglomeration’s population agglomeration level and that of other metropolitan agglomerations is gradually widening. …”
-
1340
Testing set error.
Published 2025“…<div><p>This study constructs a multi-stage hybrid forecasting model using hog price time series data and its influencing factors to improve prediction accuracy. First, seven benchmark models including Prophet, ARIMA, and LSTM were applied to raw price series, where results demonstrated that deep learning models significantly outperformed traditional methods. …”