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however, before applying any regression techniques below we normalize all feature data to have zero mean and unit variance. to quantify the accuracy of each model, we use the root mean squared error (rms error) between our predicted solar intensity at any time and the actual solar intensity observed.
با این حال، قبل از استفاده از هر تکنیک رگرسیون زیر، همه داده های ویژگی را به صورت صفر و واریانس واحد عادی می کنیم. برای تعیین دقت هر مدل، ما از هر خط زمان پیش بینی شدت خورشید و شدت واقعی خورشید استفاده می کنیم.
Son Güncelleme: 2018-08-07
Kullanım Sıklığı: 1
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in britain, house prices exhibit a distinct spatial pattern over time, rising first in a cyclical upswing in the south-east and, then, spreading out over the rest of the country. this is known as the ripple effect. although previous studies have shown that, statistically, the ripple effect is a valid representation of the data, providing convincing economic explanations is less straightforward. some studies have concentrated on the role of migration; others argue that the pattern reflects different regional growth rates. this paper suggests that structural differences in regional housing markets are important. a new model of house prices for the regions in great britain is devised and estimated in which the coefficients exhibit non-random spatial patterns. the coefficients reflect structural differences between the regions and it is shown, through simulations, that the model can generate a ripple effect irrespective of regional growth patterns.
در این مقاله به بررسی خصوصیات ایستایی ، تعادل درازمدت و رابطه سرب بین قیمت مسکن منطقه ای در چین از دسامبر 2000 تا ژوئیه 2013 می پردازیم. قیمت مسکن منطقه ای در چین ترکیبی از فرآیندهای i (0) و i (1) است. شواهد مشخصی به نفع فرضیه رابطه تعادل بلند مدت در بین همه رژیم ها وجود دارد
Son Güncelleme: 2020-07-02
Kullanım Sıklığı: 1
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