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oanus id:oanus

Rã«é–¢ã™ã‚‹oanusã®ãƒ–ãƒƒã‚¯ãƒžãƒ¼ã‚¯ (66)

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Rã§ã‚³ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°ã‚¹ã‚¿ã‚¤ãƒ«ã‚’é©ç”¨ã•ã›ã‚‹æ–¹æ³• - INPUTã—ãŸã‚‰OUTPUT!
Hadleyã®æ–°åˆŠãƒšãƒ©ãƒšãƒ©è¦‹ã¦ãŸã‚‰ã‚³ãƒ¼ãƒ‡ã‚£ãƒ³ã‚°ã‚¹ã‚¿ã‚¤ãƒ«ã«é–¢ã™ã‚‹è¨˜è¼‰ãŒã‚ã£ãŸã®ã§ãƒ¡ãƒ¢ã—ã¨ãã€‚ formatR, lintrãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ãªã©ãŒã‚ã‚‹ã‚ˆã†ã§ãã‚Œãžã‚Œè©¦ã—ã¦ã¿ã‚‹ã€‚ R Packages ä½œè€…: Hadley Wickhamå‡ºç‰ˆç¤¾/ãƒ¡ãƒ¼ã‚«ãƒ¼: Oreilly & Associates Incç™ºå£²æ—¥: 2015/04/16ãƒ¡ãƒ‡ã‚£ã‚¢: ãƒšãƒ¼ãƒ‘ãƒ¼ãƒãƒƒã‚¯ã“ã®å•†å“ã‚’å«ã‚€ãƒ–ãƒã‚°ã‚’è¦‹ã‚‹ ä»¥å‰ã®Rå‹‰å¼·ä¼š@æ±äº¬ã§ç™ºè¡¨ã—ãŸ&ã•ã‚ŒãŸè³‡æ–™ã‚‚å‚è€ƒã¾ã§ã«ã€‚ Google's r style guideã®ã™ã‚ã‚ Lint_tool_with_R formatRãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ çµæ§‹å‰ã‹ã‚‰ã‚ã‚‹ãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã®ã‚ˆã†ã ã‘ã©å˜åœ¨çŸ¥ã‚‰ãªã‹ã£ãŸã€‚ä½¿ç”¨ã™ã‚‹å‰ã« An Introduction to formatR ã‚’èªã‚ã¨ã®ã“ã¨ã€‚ tidy_source() Rã‚¹ã‚¯ãƒªãƒ—ãƒˆãƒ•ã‚¡ã‚¤ãƒ«ã‚’èªè¾¼ã‚“ã§ã‚³ãƒ³ã‚½ãƒ¼ãƒ«ã«æ•´å½¢ã•ã‚ŒãŸã‚³ãƒ¼ãƒ‰ã‚’å‡ºã™ã¿ãŸã„ã€‚ã‚¯ãƒªãƒƒãƒ—ãƒœ
oanus 2015/04/19
R
ãƒªãƒ³ã‚¯
RPubs
oanus 2015/03/11
R
ãƒªãƒ³ã‚¯
H2O.ai
Note to readers: These documents are applicable to H2O v. 2.8 and prior. If you are using the current version of H2O, (H2O-3), please visit docs.h2o.ai and select "H2O 3.0" for the latest documentation. H2O is for data scientists and application developers who need fast, in-memory scala ble machine learning for smarter applications. H2O is an open source parallel processing engine for machine learn
oanus 2015/02/25
machine_leaning

R
ãƒªãƒ³ã‚¯
R6ãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã®ç´¹ä»‹â€•æ©Ÿèƒ½ã¨å®Ÿè£…
7. 6 æ—¢å˜ã®OOã‚·ã‚¹ãƒ†ãƒ â€¢ S3 â€“ ã‚¯ãƒ©ã‚¹ã¯classå±žæ€§ã¨ã—ã¦å€‹åˆ¥ã®ã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆã«å¯¾ã—ã¦è¨å®š â€¢ ãƒ•ã‚©ãƒ¼ãƒžãƒ«ãªã‚¯ãƒ©ã‚¹å®šç¾©ã¯ãªã„ â€¢ ç¶™æ‰¿ã‚‚classå±žæ€§ã§è¡Œã† â€“ ãƒ¡ã‚½ãƒƒãƒ‰ã¯ã‚¸ã‚§ãƒãƒªãƒƒã‚¯é–¢æ•° john <- list(name = "John", age = 40) class(john) <- c("Employee", "Person") # printã¯ã‚¸ã‚§ãƒãƒªãƒƒã‚¯é–¢æ•° print #> function (x, ...) #> UseMethod("print") # ãƒ¡ã‚½ãƒƒãƒ‰å®šç¾© print.Person <- function(x) { paste0("ã“ã‚“ã«ã¡ã¯ï¼Œ", x$name, "ã§ã™ï¼Ž") } # printã§å®Ÿéš›ã«å‘¼ã°ã‚Œã‚‹ã®ã¯print.Person print(john) #> [1] "ã“ã‚“ã«ã¡ã¯ï¼ŒJohnã§ã™ï¼Ž" 8. 7 æ—¢å˜ã®OOã‚·ã‚¹ãƒ†ãƒ â€¢ S
oanus 2015/02/23
R

Object-oriented
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foreachï¼‹doSNOWãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã‚’ä½¿ã£ã¦ã€ä¸¦åˆ—å‡¦ç†ã‚’ã‚„ã£ã¦ã¿ãŸ - My Life as a Mock Quant
ãªã‚“ã ã‹webå±‹ç•Œéšˆã§ã¯Hadoopã ã®Mahoutã ã®è±¡ã‚’ä½¿ã†ã ã®ä½¿ã‚ãªã„ã ã®æ¥½ã—ãã†ãªäº‹ã‚’ã‚„ã£ã¦ã„ã¦ã€ç§ã¯ã¨ã¦ã‚‚ã•ã¿ã—ãã€ãã—ã¦ã†ã‚‰ã‚„ã¾ã—ãã‚‚ãªã£ãŸã‚ã‘ã§ã™ãŒæ‰‹å…ƒã«ãã‚“ãªç«‹æ´¾ãªç’°å¢ƒãªã‚“ã¦ãªã„ã‚ã‘ã§ã€‚ã—ã‹ã—ã€ãã‚“ãªç§ã«ã‚‚ãƒžãƒ«ãƒã‚³ã‚¢ã®ãƒ‘ã‚½ã‚³ãƒ³ãŒä¸Žãˆã‚‰ã‚Œã¦ã„ã‚‹ã®ã§ãã‚Œã§è¨ˆç®—ã®ä¸¦åˆ—åŒ–ã‚’ã‚„ã£ã¦ã¿ãŸã€‚OSã¯windows XP(32bit)ã€‚ ä½¿ã†ã®ã¯çµ±è¨ˆæ•°ç†ç ”ç©¶æ‰€ã®ã‚»ãƒŸãƒŠãƒ¼ã§ãŠè–¦ã‚ã•ã‚Œã¦ã„ãŸforeachãƒ‘ãƒƒã‚±ãƒ¼ã‚¸*1ã€‚ã“ã‚Œã¯Revlution Rã®äººãŸã¡ãŒä½œã£ã¦ã„ã‚‹ã®ã§ä»Šå¾Œã¨ã‚‚ç¶™ç¶šçš„ãªé–‹ç™ºã¨é€²åŒ–ãŒæœŸå¾…ã§ãã‚‹ã¨ã®ã“ã¨ã€‚ã¾ãšã¯ã€doSNOWãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã‚‚åˆã‚ã›ã¦ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«ã€‚ install.packages("foreach") install.packages("doSNOW") foreachãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã§ã¯forãƒ«ãƒ¼ãƒ—ã®ä¸¦åˆ—åŒ–ã‚’ã—ã¦ãã‚Œã‚‹ã®ã§ã™ãŒã€å‡¦ç†ã‚’ä¸¦åˆ—åŒ–ã•ã›ãªã„ã§æ›¸ãã“ã¨ã‚‚ã§ãã‚‹ã®ã§ã¾ãš
oanus 2014/04/19
R
ãƒªãƒ³ã‚¯
Rã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.1.0ãŒãƒªãƒªãƒ¼ã‚¹ï½œColorless Green Ideas
çµ±è¨ˆå‡¦ç†è¨€èªžã® R ã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.1.0ãŒã€2014å¹´4æœˆ10æ—¥ã«å…¬é–‹ã•ã‚ŒãŸã€‚ã“ã®æ–°ãƒªãƒªãƒ¼ã‚¹ã§ã®ä¸»ãªå¤‰æ›´ç‚¹ã«ã¤ã„ã¦è§£èª¬ã™ã‚‹ã€‚ ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.1.0ã®ãƒªãƒªãƒ¼ã‚¹ 2014å¹´4æœˆ10æ—¥ã€R ã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.1.0ãŒãƒªãƒªãƒ¼ã‚¹ã•ã‚ŒãŸã€‚ã‚³ãƒ¼ãƒ‰ãƒãƒ¼ãƒ ã¯ Spring Danceï¼ˆæ˜¥ã®è¸Šã‚Šï¼‰ã§ã‚ã‚‹ã€‚ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.0.0ãŒãƒªãƒªãƒ¼ã‚¹ã•ã‚ŒãŸã®ã¯ã€2013å¹´4æœˆ3æ—¥ãªã®ã§ã€ãŠã‚ˆã1å¹´ã‚’çµŒã¦ãƒžã‚¤ãƒŠãƒ¼ãƒãƒ¼ã‚¸ãƒ§ãƒ³ã‚¢ãƒƒãƒ—ãŒè¡Œã‚ã‚ŒãŸã“ã¨ã«ãªã‚‹ [1] ã€‚ Rã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.1.0ã®ã‚³ãƒ¼ãƒ‰ãƒãƒ¼ãƒ ã¯ Spring Danceï¼ˆæ˜¥ã®è¸Šã‚Šï¼‰ã§ã‚ã‚‹ã€‚ [2] ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.1.0ã§ã®å¤‰æ›´ç‚¹ã®è©³ç´°ã¯ã€Rã‚¢ãƒŠã‚¦ãƒ³ã‚¹ãƒ¡ãƒ¼ãƒªãƒ³ã‚°ãƒªã‚¹ãƒˆã§ã®ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.1.0ãƒªãƒªãƒ¼ã‚¹ã®é€šçŸ¥ï¼ˆR 3.1.0 is releasedã€è‹±èªžï¼‰ã‚’å‚ç…§ã•ã‚ŒãŸã„ã€‚ ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.1.0ã§ã®ä¸»ãªå¤‰æ›´ç‚¹ ä»¥ä¸‹ã§ã€ãƒãƒ¼ã‚¸ãƒ§ãƒ³3.1.0ã§ã®å¤‰æ›´ç‚¹ã®ã†ã¡ã€é‡è¦ã ã¨æ€ã‚ã‚Œã‚‹ç‚¹ã‚’ã„
oanus 2014/04/14
R

clustering
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ãƒ‘ãƒƒã‚±ãƒ¼ã‚¸gplotsã«ã¯åˆ†å‰²è¡¨ã®ã‚»ãƒ«ã®åº¦æ•°ã‚’æ°—çƒã®å¤§ãã•ã§ç¤ºã™é–¢æ•°balloonplotãŒã‚ã‚‹ã€‚ãƒ‘ãƒƒã‚±ãƒ¼ã‚¸gplotsã¯CRANãƒŸãƒ©ãƒ¼ã‚µã‚¤ãƒˆã‹ã‚‰ãƒ€ã‚¦ãƒ³ãƒãƒ¼ãƒ‰ã§ãã‚‹ã€‚balloonplotãŒæ‰±ã†ã‚ªãƒ–ã‚¸ã‚§ã‚¯ãƒˆã¯tableå½¢å¼ã§ã‚ã‚‹ã€‚æ°—çƒã®å½¢çŠ¶ã€è‰²ã¯ã€ãã‚Œãžã‚Œå¼•æ•°dotchart, dotcolorã§æŒ‡å®šã™ã‚‹ã“ã¨ãŒã§ãã‚‹ã€‚æ°—çƒã‚°ãƒ©ãƒ•ã¯å‘¨è¾ºåº¦æ•°ã‚‚è¡¨ç¤ºã™ã‚‹ã€‚åˆ†å‰²è¡¨ã®æ°—çƒã‚°ãƒ©ãƒ•ã®ä¾‹ã‚’æ¬¡ã«ç¤ºã™ã€‚ãƒ‡ãƒ¼ã‚¿ã¯Arthritisã‚’ç”¨ã„ã‚‹ã“ã¨ã«ã™ã‚‹ã€‚ > library(gplots); > library(vcd);data(Arthritis) > ArtTI <- xtabs(~ Treatment + Improved, data = Arthritis) > balloonplot(t(ArtTI))ã€€#ã‚°ãƒ©ãƒ•ã®ä½œæˆ
oanus 2012/12/06
R

ternary_plots
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HardyWeinbergãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã‚’ä½¿ã£ã¦ã¿ã‚‹ - ryamada ã®å¼Ÿåæ—¥è¨˜ï¼ˆéºä¼å¦ãƒ»çµ±è¨ˆéºä¼å¦ã®ãƒ¡ãƒ¢ï¼‰
oanus 2012/12/06
R

ternary_plots
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ã¯ã˜ã‚ã« å¤šé …åˆ†å¸ƒã«ã‚ˆã‚‹ä¿¡é ¼é ˜åŸŸ ä¸‰æˆåˆ†ã®å¤šé …ä¿¡é ¼é ˜åŸŸ ä½¿ç”¨ä¾‹ å¤šå¤‰é‡åŠ æ³•ãƒã‚¸ã‚¹ãƒ†ã‚£ãƒƒã‚¯æ£è¦åˆ†å¸ƒã«ã‚ˆã‚‹ä¿¡é ¼é ˜åŸŸ ä¸‰æˆåˆ†ã®åŠ æ³•ãƒã‚¸ã‚¹ãƒ†ã‚£ãƒƒã‚¯æ£è¦ä¿¡é ¼é ˜åŸŸ ä½¿ç”¨ä¾‹ ã¯ã˜ã‚ã« åœ°è³ªå¦ã®åˆ†é‡Žã§ã¯ï¼Œã•ã¾ã–ã¾ãªçµ„æˆãƒ‡ãƒ¼ã‚¿ã‚’ä¸‰è§’ãƒ€ã‚¤ã‚¢ã‚°ãƒ©ãƒ ã«ãƒ—ãƒãƒƒãƒˆã™ã‚‹ã“ã¨ãŒã‚ã‚Šã¾ã™ï¼Žã“ã®ã¨ãï¼Œãã®çµ„æˆãƒ‡ãƒ¼ã‚¿ãŒã‚°ãƒ©ãƒ•ã®ä¸ã®ã©ã®ç¨‹åº¦ã®ç¯„å›²ã«åˆ†å¸ƒã™ã‚‹ã®ã‹ã‚’çŸ¥ã‚ŠãŸã„ã“ã¨ãŒã‚ã‚Šã¾ã™ï¼Žå¾“æ¥ã¯ï¼Œã“ã®ç¯„å›²ã‚’ãƒ•ãƒªãƒ¼ãƒãƒ³ãƒ‰ã§æã„ãŸã‚Šï¼Œå¹³å‡å€¤ã¨æ¨™æº–åå·®ã‹ã‚‰è¨ˆç®—ã—ãŸå…è§’å½¢ã®é ˜åŸŸã‚’æãã“ã¨ãŒè¡Œã‚ã‚Œã¦ãã¾ã—ãŸï¼Žã—ã‹ã—ï¼Œã“ã‚Œã‚‰ã®æç”»æ–¹æ³•ã¯ï¼Œæ£æ„çš„ã§ã‚ã£ãŸã‚Šï¼Œçµ±è¨ˆçš„ã«ä¸ååˆ†ã§ã‚ã‚‹ã¨ã„ã†å•é¡ŒãŒã‚ã‚Šã¾ã—ãŸ (Weltje, 2002)ï¼Ž ä¸‰æˆåˆ†ã®çµ„æˆãƒ‡ãƒ¼ã‚¿ã«å¯¾ã—ï¼Œçµ±è¨ˆçš„ã«åŽ³å¯†ãªä¿¡é ¼é ˜åŸŸã‚’æãã“ã¨ã¯Aitchison (1986)ï¼ˆã¾ãŸã¯ï¼ŒAitchison 2003ï¼‰ã‚„Weltje (2002)ã«ã‚ˆã£ã¦æ§‹ç¯‰ã•ã‚Œã¦ãã¾ã—ãŸï¼Žã“ã“ã§ã¯ï¼ŒWeltje (20
oanus 2012/12/06
R

ternary_plots
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Drawing ternary diagrams (ternary plots)
ä¸‰è§’ãƒ€ã‚¤ã‚¢ã‚°ãƒ©ãƒ ã‚’æãï¼ˆDrawing ternary diagramsï¼‰ English åœ°çƒç§‘å¦ã®åˆ†é‡Žã§ã¯2æˆåˆ†ã®xyã‚°ãƒ©ãƒ•ã«åŠ ãˆï¼Œ3æˆåˆ†ã®xyzä¸‰è§’ãƒ€ã‚¤ã‚¢ã‚°ãƒ©ãƒ ï¼ˆä¸‰è§’ã‚°ãƒ©ãƒ•ï¼‰ã‚’ã‚ˆãä½¿ã„ã¾ã™ï¼Žã“ã“ã§ã¯ä¸‰è§’ãƒ€ã‚¤ã‚¢ã‚°ãƒ©ãƒ ã«ã¤ã„ã¦ã®èª¬æ˜Žã¨ã‚°ãƒ©ãƒ•ã®æãæ–¹ã‚’ã¾ã¨ã‚ã¦ã„ã¾ã™ï¼Ž ä¸‰è§’ãƒ€ã‚¤ã‚¢ã‚°ãƒ©ãƒ ã¨ã¯ ä¸‰è§’ãƒ€ã‚¤ã‚¢ã‚°ãƒ©ãƒ ã¯ï¼Œ3æˆåˆ†ã®ãƒ‡ãƒ¼ã‚¿ã‚’ä¸‰è§’å½¢ã®ã‚°ãƒ©ãƒ•ã«ãƒ—ãƒãƒƒãƒˆã—ãŸã‚‚ã®ã§ã™ï¼Ž3æˆåˆ†ã®ç›¸å¯¾çš„ãªå‰²åˆï¼ˆçµ„æˆãƒ‡ãƒ¼ã‚¿ï¼‰ã«ã‚ˆã£ã¦ï¼Œä¸‰è§’å½¢ã®ä¸ã®ä½ç½®ãŒæ±ºã¾ã‚Šã¾ã™ï¼Žãƒ—ãƒãƒƒãƒˆã•ã‚ŒãŸç‚¹ã‹ã‚‰å„è¾ºã¸ãŠã‚ã—ãŸç·šã®ä½ç½®ãŒï¼Œãã‚Œãžã‚Œã®æˆåˆ†ã®å¤§ãã•ã‚’ç¤ºã—ã¦ã„ã¾ã™ï¼ˆå›³1ï¼‰ï¼Žä¾‹ãˆã°ï¼Œå›³ä¸ã®ç‚¹Pã¯ï¼ŒXYZæˆåˆ†ã®æ¯”ãŒ0.2:0.2:0.6ã«ãªã£ã¦ã„ã¾ã™ï¼Ž ã‚°ãƒ©ãƒ•ã‚’æãã«ã¯ï¼Œ3æˆåˆ† (x, y, z) ã®ãƒ‡ãƒ¼ã‚¿ã‚’X-Yåº§æ¨™ã§æã‘ã‚‹ã‚ˆã†ã«2æˆåˆ† (X, Y) ã«å¤‰æ›ã—ã¾ã™ï¼Žã“ã“ã§ï¼Œä¸‰è§’ãƒ€ã‚¤ã‚¢ã‚°ãƒ©ãƒ ã¯ï¼ˆx, y, zï¼‰ã‚’å·¦ä¸‹ã‹ã‚‰åæ™‚è¨ˆå›žã‚Šã«ãƒ—ãƒãƒƒãƒˆ
oanus 2012/12/06
R

ternary_plots
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ä½¿ç”¨ã™ã‚‹ã‚½ãƒ•ãƒˆã‚„Rãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã«ã‚ˆã£ã¦ã‚¯ãƒãƒ³ãƒãƒƒã‚¯ã®Î±ä¿¡é ¼æ€§ä¿‚æ•°ãŒç•°ãªã‚‹ã¨ã„ã†ã“ã¨ã«ã¤ã„ã¦ï¼Œ@casualconcã•ã‚“ã‹ã‚‰ã”æŒ‡æ‘˜ãŒã‚ã‚Šã¾ã—ãŸã€‚é …ç›®-å…¨ä½“å¾—ç‚¹ç›¸é–¢ãŒãƒžã‚¤ãƒŠã‚¹ã«ãªã‚‹é …ç›®ã‚’ï¼ŒRã®psychãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã®alpha()ã¨Stataã§ã¯ï¼Œè‡ªå‹•çš„ã«é€†è»¢é …ç›®ã¨ã—ã¦ä¿®æ£ã—ã¦ã—ã¾ã†ã“ã¨ãŒåŽŸå› ã ã¨ã‚ã‹ã‚Šã¾ã—ãŸã€‚ ï¼œé€†è»¢é …ç›®ã®å‡¦ç†ã‚’è‡ªå‹•çš„ã«ã—ãªã„ã‚‚ã®ï¼ž - Rã®ltmãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ cronbach.alpha() - SPSS ç¶šãã‚’èªã‚€
oanus 2012/10/20
R

software

statistics

ã‚ã‚‹ã‚ã‚‹
ãƒªãƒ³ã‚¯
plotkml
oanus 2012/09/24
GIS

R
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Rè¨€èªžã«ã‚ˆã‚‹å¤šå¤‰é‡æ™‚ç³»åˆ—åˆ†æžâˆ’Dynamic Conditional Correlation GARCH Model - hamadakoichi blog
Rè¨€èªžã«ã‚ˆã‚‹å¤šå¤‰é‡æ™‚ç³»åˆ—åˆ†æžã€‚ è¤‡æ•°ã‚°ãƒ«ãƒ¼ãƒ—ãƒ»è¤‡æ•°é …ç›®ã®æ™‚ç³»åˆ—ãƒ‡ãƒ¼ã‚¿ã§æ™‚ç³»åˆ—é–“ã®é–¢ä¿‚æ€§ãƒ»å½±éŸ¿ã‚’æ˜Žã‚‰ã‹ã«ã™ã‚‹ã€‚ ä»¥ä¸‹ã€å®Ÿè¡Œå¯èƒ½ãªRè¨€èªžã‚½ãƒ¼ã‚¹ã‚³ãƒ¼ãƒ‰ã‚’ç”¨ã„ç´¹ä»‹ã™ã‚‹ã€‚ ä¾‹ï¼šè¤‡æ•°æ™‚ç³»åˆ—é–“ã®é–¢ä¿‚æ€§ãƒ»å½±éŸ¿ è¾²å®¶ã”ã¨ã®è¾²åœ°ã®è‚¥æ²ƒåº¦ãƒ»äººã®å„ä»•äº‹ã®åŠ´åƒé‡ãƒ»å„è‚¥æ–™ã®æŠ•å…¥é‡ã®å„æ™‚ç³»åˆ—ã€ãŠã‚ˆã³ã€ç”Ÿç”£é‡ã®æ™‚ç³»åˆ—ã‹ã‚‰ã€è‚¥æ²ƒåº¦ãƒ»å„åŠ´åƒé‡ãƒ»å„è‚¥æ–™é‡ãŒç”Ÿç”£é‡ã«ä¸Žãˆã‚‹å½±éŸ¿ã‚’æ˜Žã‚‰ã‹ã«ã™ã‚‹ã€‚ å›½ã”ã¨ã®å„æ”¿ç–ç¨®é¡žã¸ã®æŠ•è³‡é¡ã®æ™‚ç³»åˆ—ã€ãŠã‚ˆã³ã€GDP ã‹ã‚‰ã€å„æ”¿ç–æŠ•è³‡ãŒGDPã«ä¸Žãˆã‚‹å½±éŸ¿ã‚’æ˜Žã‚‰ã‹ã«ã™ã‚‹ åœ°åŸŸã”ã¨ã®å„ã‚ãƒ£ãƒ³ãƒšãƒ¼ãƒ³ç¨®é¡žã®æŠ•å…¥é‡ã®å„æ™‚ç³»åˆ—ã€ãŠã‚ˆã³ã€å•†å“å£²ä¸Šã®æ™‚ç³»åˆ—ã‹ã‚‰ã€å„åœ°åŸŸã®å„ã‚ãƒ£ãƒ³ãƒšãƒ¼ãƒ³ãŒå£²ä¸Šã«ä¸Žãˆã‚‹å½±éŸ¿ã‚’æ˜Žã‚‰ã‹ã«ã™ã‚‹ã€‚ç‰ã€‚ Rè¨€èªžã«ã‚ˆã‚‹æ™‚ç³»åˆ—åˆ†æžå…¥é–€ Rè¨€èªžã§ã®ARã€ARMA/ARIMAã€ARFIMAã€ARCHã€ãªã©ã®æ™‚ç³»åˆ—ãƒ¢ãƒ‡ãƒ«ã®å…¥é–€è³‡æ–™ï¼ˆâ€»ï¼‘å¹´å‰ã®Tokyo.R è¬›å¸«è³‡æ–™) http://d.hatena.ne.j
oanus 2012/08/15
R

timeseries_analysis
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Rã§ãƒžã‚¼ãƒ³ã‚¿-é»’-ç·‘ã«ãªã‚‹ãƒãƒªã‚¢ãƒ•ãƒªãƒ¼ãªã‚«ãƒ©ãƒ¼ãƒ‘ãƒ¬ãƒƒãƒˆã‚’ç”Ÿæˆã™ã‚‹
ãƒãƒªã‚¢ãƒ•ãƒªãƒ¼ãªãƒ’ãƒ¼ãƒˆãƒžãƒƒãƒ—ã‚’æããŸã‚ã«ã€ãƒžã‚¼ãƒ³ã‚¿-é»’-ç·‘ã®ã‚«ãƒ©ãƒ¼ãƒ‘ãƒ¬ãƒƒãƒˆãŒä½¿ã„ãŸã‹ã£ãŸã®ã§ã™ãŒã€R ã§ã©ã†ã‚„ã£ã¦è‰¯ã„ã®ã‹ã‚ã‹ã‚‰ãªã‹ã£ãŸã®ã§è‡ªä½œã—ã¾ã—ãŸã€‚ç°¡å˜ãªæ–¹æ³•ã‚’çŸ¥ã£ã¦ã„ã‚‹äººãŒã„ã‚Œã°æ•™ãˆã¦ãã ã•ã„ã€‚ [code] magentablackgreen <- function(n) { r <- c( round( seq.int(236, 0, by=-236/(n-1)) ), rep(0, n) ) g <- c( rep(0, n), round( seq.int(0, 255, by=255/(n-1)) ) ) b <- c( round( seq.int(140,0, by=-140/(n-1)) ), rep(0, n) ) rgb(r, g, b, max=255) } [/code] [code] cols <- magentablackgreen(25) [/code]
oanus 2012/06/26
R

coloring
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Excelä¸Šã§Rã‚’å‹•ã‹ã™RExcel - ã‚‚ã†ã‚«ãƒ„ä¸¼ã§ã„ã„ã‚ˆãª
æœ€è¿‘Office Professionalã‚’è²·ã£ãŸã®ã§ï¼Œè¿‘é ƒã¯ã‚‚ã£ã±ã‚‰Officeã§éŠã‚“ã§ã„ã‚‹ï¼ŽOfficeã¯ã¡ã‚‡ã£ã¨ãƒã‚°ã¨ã‹å¤šãã¦é›£ã—ã„ã‹ã‚‰ï¼Œã‚ˆãå‹‰å¼·ã‚’ã—ã¦æ—©ãåˆå¿ƒè€…ã‚’è„±å‡ºã—ãŸã„ï¼Ž ã§ï¼Œã“ã“2ã€œ3æ—¥ã¯Excelã‹ã‚‰Rã‚’å‘¼ã¶æ–¹æ³•ã‚’ã„ã‚ã„ã‚èª¿ã¹ã¦ã„ãŸï¼Žã‚„ã£ã±VBAã¡ã‚‡ã£ã¨ãã‚‰ã„å‹‰å¼·ã—ãªã„ã¨é§„ç›®ã‹ãªã¨ã‹æ€ã„å§‹ã‚ãŸé ƒï¼ŒRExcelã¨ã„ã†Excelã®ã‚¢ãƒ‰ã‚¤ãƒ³ã‚’è¦‹ã¤ã‘ãŸ(statconn)ï¼Žã“ã‚Œã‚’ä½¿ã†ã¨çµæ§‹å®Ÿç”¨çš„ãªãƒ¬ãƒ™ãƒ«ã§Excelã¨Rã‚’é€£æºã•ã›ã‚‰ã‚Œãã†*1ï¼Ž RExcelã®ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ« ã¾ãšï¼Œrscproxyã¨rcomã®2ã¤ã®ãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã‚’Rã‹ã‚‰å…¥ã‚Œã¦ãŠãï¼Žä¸‹ã®äºŒè¡Œã¯RExcelã®ã‚¤ãƒ³ã‚¹ãƒˆãƒ¼ãƒ«æ™‚ã«ã‚„ã‚Œã£ã¦ã„ã‚ã‚ŒãŸã‹ã‚‰ã‚„ã£ãŸ*2ï¼Ž install.packages("rscproxy") install.packages("rcom") library(rcom) comRegisterRegistr
oanus 2012/05/10
excel

R
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MTè·é›¢ã£ã¦ã®ãŒã„ã¾ã„ã¡ã¤ã‹ã‚ã¦ãªã„
CRANã®NewsletterãŒæ›´æ–°ã•ã‚Œã¦ã„ãŸã®ã§ã€ä¸€æ˜¨æ—¥ã®å¸°ã‚Šã®æ–°å¹¹ç·šã®ä¸ã§èªã‚“ã§ãŸã‚‰ã€fingerprintã£ã¦ã„ã†ãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ãŒè¿½åŠ ã•ã‚Œã¦ãŸã€‚ CRAN - Package fingerprint This package contains functions to manipulate binary fingerprints of arbitrary length. A fingerprint is represented by an object of S4 class 'fingerprint' which is internally represented a vector of integers, such that each element represents the position in the fingerprint that is set to 1. The bi
oanus 2012/05/04
R

statistics

distance
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ä¸‰æ¬¡å…ƒæ•£å¸ƒå›³ã‚’Rã§æãã®ã«ç”»æœŸçš„ãªæ–°æ©Ÿèƒ½ãŒRGLãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã«åŠ ã‚ã£ãŸ - ã»ããç¬‘ã‚€
ä»¥å‰ã€ä¸‰æ¬¡å…ƒæ•£å¸ƒå›³ã‚’Rã§æã„ã¦ã¿ãŸã¨ã„ã†è¨˜äº‹ã§ç´¹ä»‹ã—ãŸRGLãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã«ç”»æœŸçš„ãªæ–°æ©Ÿèƒ½ãŒåŠ ã‚ã£ãŸã®ã§ç´¹ä»‹ã—ã¾ã™ã€‚ (æƒ…å ±æºï¼šR: Interactive 3D WebGL plot of time-space cube with RGL | geolabs) RGLãƒ‘ãƒƒã‚±ãƒ¼ã‚¸ã®è‰¯ã„ã¨ã“ã‚ã¯ã€3æ¬¡å…ƒãƒ—ãƒãƒƒãƒˆã‚’ãƒžã‚¦ã‚¹ãƒ‰ãƒ©ãƒƒã‚°ã§ã‚°ãƒªã‚°ãƒªå‹•ã‹ã›ã‚‹ã¨ã“ã‚ãªã®ã§ã™ãŒã€ã„ã–ã€ãƒ•ã‚¡ã‚¤ãƒ«å‡ºåŠ›ã—ã‚ˆã†ã¨ã™ã‚‹ã¨ã€é™æ¢ç”»ã‹å‹•ç”»ã§ã—ã‹ä¿å˜ã§ããšã€ã‚¤ãƒ³ã‚¿ãƒ©ã‚¯ãƒ†ã‚£ãƒ–ãª3æ¬¡å…ƒãƒ—ãƒãƒƒãƒˆã‚’ãã®ã¾ã¾ãƒ•ã‚¡ã‚¤ãƒ«ã«ä¿å˜ã™ã‚‹ã“ã¨ãŒã§ããªã„ã¨ã„ã†ã®ãŒæ¬ ç‚¹ã§ã—ãŸã€‚ ã—ã‹ã—ä»Šå›žã€æ–°æ©Ÿèƒ½ã¨ã—ã¦ã€WebGL ã§å‹•ã HTML ãƒ•ã‚¡ã‚¤ãƒ«ã¨ã—ã¦ä¿å˜ã§ãã‚‹æ©Ÿèƒ½ãŒä»˜åŠ ã•ã‚ŒãŸã‚ˆã†ã§ã™ã€‚ ã•ã£ããè©¦ã—ã¦ã¿ã¾ã—ã‚‡ã†ã€‚ install.packages("rgl") library("rgl") data(trees) plot3d(trees) writeWe
oanus 2012/04/25
R

visualization
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R ã«ãŠã‘ã‚‹ãƒã‚¤ãƒ‘ãƒ•ã‚©ãƒ¼ãƒžãƒ³ã‚¹ã‚³ãƒ³ãƒ”ãƒ¥ãƒ¼ãƒ†ã‚£ãƒ³ã‚°æ‰‹æ³•
. . R â€ â€¡ â€ â€¡ COM-ONE 2011 1 24 1 / 63 1 2 3 4 5 2 / 63 R R R On memory 3 / 63 CRAN Task View: High-Performance and Parallel Computing with R (Dirk Eddelbuettel ) (Explicit parallelism) *,** (Implicit parallelism) *,**,*** (Grid computing) (Random numbers) *,** (Resource managers and batch schedulers) ** (Applications) * GPU (GPUs) (Large memory and out-of-memory data) * (Easier interfaces for Com
oanus 2012/03/31
R

HPC
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Taking R to the Limit, Part II â€“ Large Datasets in R
For Part I, Parallelism in R, click here. Tuesday night I again had the opportunity to present on high performance computing in R, at the Los Angeles R Usersâ€™ Group. This was the second part of a two part series called â€œTaking R to the Limit: High Performance Computing in R.â€ Part II discussed ways to work with large datasets in R. I also tied in MapReduce into the talk. Unfortunately, there was t
oanus 2012/03/31
R

HPC
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Taking R to the Limit, Part I â€“ Parallelization in R
oanus 2012/03/31
R

HPC
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