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Titlebook: An Introduction to R for Quantitative Economics; Graphing, Simulating Vikram Dayal Book 2015 The Author(s) 2015 Applied Econometrics.Quanti

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11#
發(fā)表于 2025-3-23 13:18:33 | 只看該作者
12#
發(fā)表于 2025-3-23 14:54:38 | 只看該作者
13#
發(fā)表于 2025-3-23 21:16:05 | 只看該作者
Ankerwicklungen und Stromwendung,This book emphasizes three key skills—graphing, computing and simulating. We develop these skills in the context of such models as supply and demand, and the Solow growth model, moving between theory and data.
14#
發(fā)表于 2025-3-24 00:35:18 | 只看該作者
Vereinigung der Gro?kesselbesitzer E.V.We see how to get data into R with three examples. We like to convert the data into a csv (comma-separated values) file and then get it into RStudio. We see how we can have a quick look at the data in RStudio. We will work with these three datasets in later chapters.
15#
發(fā)表于 2025-3-24 05:09:11 | 只看該作者
16#
發(fā)表于 2025-3-24 07:09:32 | 只看該作者
https://doi.org/10.1007/978-3-642-99933-8We use the mosaic package to view a two input function—the Cobb-Douglas function—from different angles. We see how in the Cobb-Douglas production function output as a function of labour changes as we change the amount of capital or the level of technology. We see how we can graph isoquants.
17#
發(fā)表于 2025-3-24 13:03:53 | 只看該作者
https://doi.org/10.1007/978-3-642-99933-8We combine matrix algebra computations with those of statistics. We first use R for some simple vector operations relating to variances and covariances. Then, we look at some simple matrix operations. Finally, we use matrix operations in R for regression.
18#
發(fā)表于 2025-3-24 15:07:53 | 只看該作者
Die Wiederentdeckung der DiasporaWe use R to generate synthetic data from different probability distributions. We then generate data and use simple regression and a t-test on this data. Finally, we simulate logit regression.
19#
發(fā)表于 2025-3-24 20:22:01 | 只看該作者
Die Wiederentdeckung der DiasporaWe look at Anscombe’s, (Am Stat 27(1):17–21, .) data which is one of the datasets that come with the R software. We compute different linear regressions of Anscombe’s four sets of data—they give us the same results. When we look at the scatterplots corresponding to Anscombe’s four sets of data we see that they are very different.
20#
發(fā)表于 2025-3-25 00:42:07 | 只看該作者
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