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Intuition for an Old Curiosity and an Implication for MCMC
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| Pengarang | : | - |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 75 (No. 1) |
| Halaman | : | 1-6 |
| Abstrak | : | Morris and Ebey reported the following curiosity. “The unweighted sample mean is examined as an estimator of the population mean in a first-order autoregressive model. It is demonstrated that the precision of this estimator deteriorates as the number of equally spaced observations taken within a fixed time interval increases.” Morris and Ebey proved their result but gave no intuition for it. We provide some intuition, then examine an implication: that the usual practice of estimating posterior expectations by taking the unweighted average of consecutive Markov chain Monte Carlo (MCMC) samples may not be optimal. |
Sistem pemerintahan berbasis elektronik dalam meningkatkan daya saing di daerah
| Pengarang | : | |
| Nama Majalah/Jurnal | : | Analisis CSIS |
| Volume / Edisi | : | 52 (No. 4) |
| Halaman | : | 643-662 |
| Abstrak | : | Sistem Pemerintahan Berbasis Elektronik (SPBE) merupakan sebuah tata kelola yang sedang diupayakan oleh seluruh instansi pemerintahan di Indonesia. Dengan tujuan untuk digitalisasi tata kelola, penerapan SPBE dilakukan secara bolistik pada lapisan-lapisan yang ada. termasuk dalam pemerintahan daerah. Berdasarkan Indeks Daya Saing Daerah Berkelanjutan (IDSDB), pelaksanaan SPBE merupakan determinan dari sebutah governasi yang berjalan efektif, sehingga menjadi salah satu indikator untuk menentukan suatu daerah memiliki daya saing yang tinggi khususnya dalam pilar tata kelola berkelanjutian. Meskipun demikian, masih banyak pemerintah daerah yang belum siap melaksanakan SPBE di daerahnya. Melalui penelitian ini akan dibahas, bagaimana pelaksanaan SPBE daerah berdasarkan kewajiban dan kewenangan dari masing-masing pemerintahan di daerah, bisa saling berkaitan dalam meningkatkan daya saing daerah. Peningkatan daya saing daerah berkelanjutan melalui SPBE bukan hanya menciptakan pelayanan publik yang efisianakan tetapi juga meningkatkan pelayanan yang kondusif bagi investasi dan perkembangan sektor swasta. |
The Impact of Application of the Jackknife to the Sample Median
| Pengarang | : | Jianning Yang |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 75 (No. 4) |
| Halaman | : | 445-449 |
| Abstrak | : | The jackknife is a reliable tool for reducing the bias of a wide range of estimators. This note demonstrates that even such versatile tools have regularity conditions that can be violated even in relatively simple cases, and that caution needs to be exercised in their use. In particular, we show that the jackknife does not provide the expected reliability for bias-reduction for the sample median, because of subtle changes in behavior of the sample median as one moves between even and odd sample sizes. These considerations arose out of class discussions in a MS-level nonparametrics course. |
Facilitating Authentic Practice for Early Undergraduate Statistics Students
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 75 (No. 4) |
| Halaman | : | 433-444 |
| Abstrak | : | In current curricula, authentic statistical practice generally only occurs in capstone projects undertaken by advanced undergraduate and Master’s students. We argue that deferring practice is a mistake: undergraduate students should achieve experience via repeated practice from their first years onward, to achieve heightened levels of confidence and competence prior to graduation. However, statistical practice is not a “one size fits all” enterprise: for instance, elements of a capstone experience, such as extensive data preprocessing, may be out of place in earlier practice settings due to less-experienced students’ relative lack of coding skill. We describe a course we have implemented at Carnegie Mellon University, currently open to second-year students, that provides a circumscribed opportunity for statistical practice that limits coding breadth, uses fully curated data, treats statistical learning models as “gray boxes” to be understood qualitatively, and provides open-ended semester-long projects that students pursue outside of class. We show how pre- and post-course assessment tests and retrospective surveys indicate clear gains in the students’ knowledge of, and attitudes toward, statistical practice. Given its clear benefits, we feel that statistics and data science programs should offer a course like the one we describe to all undergraduate students pursuing statistics and data science degrees. |
A Review of Bayesian Perspectives on Sample Size Derivation for Confirmatory Trials
| Pengarang | : | Kevin Kunzmann |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 75 (No. 4) |
| Halaman | : | 424-432 |
| Abstrak | : | Sample size derivation is a crucial element of planning any confirmatory trial. The required sample size is typically derived based on constraints on the maximal acceptable Type I error rate and minimal desired power. Power depends on the unknown true effect and tends to be calculated either for the smallest relevant effect or a likely point alternative. The former might be problematic if the minimal relevant effect is close to the null, thus requiring an excessively large sample size, while the latter is dubious since it does not account for the a priori uncertainty about the likely alternative effect. A Bayesian perspective on sample size derivation for a frequentist trial can reconcile arguments about the relative a priori plausibility of alternative effects with ideas based on the relevance of effect sizes. Many suggestions as to how such “hybrid” approaches could be implemented in practice have been put forward. However, key quantities are often defined in subtly different ways in the literature. Starting from the traditional entirely frequentist approach to sample size derivation, we derive consistent definitions for the most commonly used hybrid quantities and highlight connections, before discussing and demonstrating their use in sample size derivation for clinical trials. |
Pairwise Comparisons Using Ranks in the One-Way Model
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 75 (No. 4) |
| Halaman | : | 414-423 |
| Abstrak | : | The Wilcoxon rank sum test for two independent samples and the Kruskal–Wallis rank test for the one-way model with k independent samples are very competitive robust alternatives to the two-sample t-test and k-sample F-test when the underlying data have tails longer than the normal distribution. However, these positives for rank methods do not extend as readily to methods for making all pairwise comparisons used to reveal where the differences in location may exist. Here, we show that the closed method of Marcus et al. applied to ranks is quite powerful for both small and large samples and better than any methods suggested in the list of applied nonparametric texts found in the recent study by Richardson. In addition, we show that the closed method applied to means is even more powerful than the classical Tukey–Kramer method applied to means, which itself is very competitive for nonnormal data with moderately long tails and small samples. |
Learning Hamiltonian Monte Carlo in R
| Pengarang | : | Leonard Dekens |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 75 (No. 4) |
| Halaman | : | 403-413 |
| Abstrak | : | Hamiltonian Monte Carlo (HMC) is a powerful tool for Bayesian computation. In comparison with the traditional Metropolis–Hastings algorithm, HMC offers greater computational efficiency, especially in higher dimensional or more complex modeling situations. To most statisticians, however, the idea of HMC comes from a less familiar origin, one that is based on the theory of classical mechanics. Its implementation, either through Stan or one of its derivative programs, can appear opaque to beginners. A lack of understanding of the inner working of HMC, in our opinion, has hindered its application to a broader range of statistical problems. In this article, we review the basic concepts of HMC in a language that is more familiar to statisticians, and we describe an HMC implementation in R, one of the most frequently used statistical software environments. We also present hmclearn, an R package for learning HMC. This package contains a general-purpose HMC function for data analysis. We illustrate the use of this package in common statistical models. In doing so, we hope to promote this powerful computational tool for wider use. Example code for common statistical models is presented as supplementary material for online publication. |
Peran pedesaan dalam mendukung ketahanan pangan nasional
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | Analisis CSIS |
| Volume / Edisi | : | 52 (No. 4) |
| Halaman | : | 617-642 |
| Abstrak | : | Pangan merupakan kebutuhan dasar dan paling utama dalam pemenuhan dasar kebutuhan manusia yang dijamin dalam Undang-Undang Dasar 1945 . Ketahanan pangan masih dihadapkan pada sejumlah masalah, baik pada ketersediaan pangan aksesibilitas terhadap pangan dan kualitas serta kemanfaatan pangan. Ketersediaan pangan masih dihadapkan pada fenomena mahalnya harga pangan, penurunan luas lahan pertanian, impor pangan yang tinggi dan minim bilirisasi pertanian. Persoalan akses pangan juga belum merata pada tiap daerah, baik di pedesaan maupun di perkotaan yang berimplikasi pada peningkatan resiko kekurangan gizi dan stunting pada anak-anak. Kemanfaatan pangan dan kualitas pangan yang dilihat dari konsumsi energi juga masih dibawah standar dan tidak layak konsumsi. Intervensi kebijakan pemerintah dalam mendukung ketahanan pangan dilihat dari jumlah ketersediaan pangan yang cukup dalam negeri. Di sisi lain, penguatan peran desa menjadi sangat krusial sebagai sumber dan lokus pangan itu berada. Penguatan desa sebagai lumbung pangan perlu mengidentifikasi potensi desa pemberdayaan masayarakat tani dan penguatan kelompok tani, transfer knowledge dan teknologi penguatan infrastruktur penunjang, membentuk lumbung pangan desa untuk menjamin ketersediaan stok pangan, memanfaatkian Bumdes untuk pemasaran hasil produk pertanian, distribusi pangan desa dan mendorong partisipasi aktif warga desa melek pangan untuk kebutuhan keluarga. |
Random number generators produce collisions: Why, how many and more
| Pengarang | : | - |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 75 (No. 4) |
| Halaman | : | 394-402 |
| Abstrak | : | It seems surprising that when applying widely used random number generators to generate one million random numbers on modern architectures, one obtains, on average, about 116 collisions. This article explains why, how to mathematically compute such a number, why they often cannot be obtained in a straightforward way, how to numerically compute them in a robust way and, among other things, what would need to be changed to bring this number below 1. The probability of at least one collision is also briefly addressed, which, as it turns out, again needs a careful numerical treatment. Overall, the article provides an introduction to the representation of floating-point numbers on a computer and corresponding implications in statistics and simulation. All computations are carried out in R and are reproducible with the texttt included in this article. |
Hurdle Blockmodels for Sparse Network Modeling
| Pengarang | : | Narges Motalebi |
| Nama Majalah/Jurnal | : | The American Statistician |
| Volume / Edisi | : | 75 (No. 4) |
| Halaman | : | 383-393 |
| Abstrak | : | A variety of random graph models have been proposed in the literature to model the associations within an interconnected system and to realistically account for various structures and attributes of such systems. In particular, much research has been devoted to modeling the interaction of humans within social networks. However, such networks in real-life tend to be extremely sparse and existing methods do not adequately address this issue. In this article, we propose an extension to ordinary and degree corrected stochastic blockmodels that accounts for a high degree of sparsity. Specifically, we propose hurdle versions of these blockmodels to account for community structure and degree heterogeneity in sparse networks. We use simulation to ensure parameter estimation is consistent and precise, and we propose the use of likelihood ratio-type tests for model selection. We illustrate the necessity for hurdle blockmodels with a small research collaboration network as well as the infamous Enron E-mail exchange network. Methods for determining goodness of fit and performing model selection are also proposed. Supplementary materials for this article are available online. |