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A variety of measures of national income and output are used in economics to estimate total economic activity in a country or region, including gross domestic product (GDP), gross national product (GNP), net national income (NNI), and adjusted national income (NNI adjusted for natural resource depletion – also called as NNI at factor cost). All are specially concerned with counting the total amount of goods and services produced within the economy and by various sectors. The boundary is usually defined by geography or citizenship, and it is also defined as the total income of the nation and also restrict the goods and services that are counted. For instance, some measures count only goods & services that are exchanged for money, excluding bartered goods, while other measures may attempt to include bartered goods by imputing monetary values to them. National accounts Arriving at a figure for the total production of goods and services in a large region like a country entails a large amount of data-collection and calculation. Although some attempts were made to estimate national incomes as long ago as the 17th century, the systematic keeping of national accounts, of which these figures are a part, only began in the 1930s, in the United States and some European countries. The impetus for that major statistical effort was the Great Depression and the rise of Keynesian economics, which prescribed a greater role for the government in managing an economy, and made it necessary for governments to obtain accurate information so that their interventions into the economy could proceed as well-informed as possible. Market value In order to count a good or service, it is necessary to assign value to it. The value that the measures of national income and output assign to a good or service is its market value – the price it fetches when bought or sold. The actual usefulness of a product (its use-value) is not measured – assuming the use-value to be any different from its market value.
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As the variables contained in a cell are stor [2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will implement a simple fractional resampler that
uses local Lagrange interpolation. The resampler can be used to perform
any rational sampling rate change (but beware of aliasing when
downsampling!)
In [1]:
import numpy as np
import IPython
from scipy.io import wavfile
Local Lagrange interpolation[4]¶
To perform resampling we will need to compute subsample values and, in [2]Paolo Prandoni, [3]LCAV, EPFL
In this notebook we will explore various ways to implement a system
that changes the voice of a speaker. Typical applications for these
techniques, strictly sorted by plausibility, include international spy
missions and prank telephone calls, and devices such as the one
displayed here can be easily bought on the web... or in a novelty shop.
No description has been provided for t [2]Paolo Prandoni, [3]LCAV, EPFL
In [1]:
import matplotlib.pyplot as plt
import numpy as np
import scipy.signal as sp
import seaborn as sns
sns.set()
In [2]:
plt.rcParams["figure.figsize"] = (14,4)
The basic reproduction number[4]¶
The propagation mechanism of an epidemic such as the one caused by
SARS-CoV-2 virus can be roughly modeled, at least in its inital phase,
as a process in which each infected individ